Full-Stack Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT

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Full-Stack Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT

About Veridue AI / the mission we obsess over Energy is the primary lever for the survival of our planet. The transition to a

zero-carbon economy is the greatest challenge of our generation, touching

everything from global affordability to the massive power demands of the AI

revolution.

Our mission is simple: Abundant, cheap, and clean energy for everyone.

To stay within a livable climate threshold, the world must invest $4 trillion every

single year in energy transition infrastructure: renewables, battery storage, and

EV charging. Currently, we are failing to hit that target.

The bottleneck isn't a lack of capital, the cost of hardware, or the speed of

construction. The bottleneck is automatable processes. On average, it takes five

years to get all the paperwork in place to build a one-year construction project.

The world is building paper stacks, instead of solar racks.

We are building the AI infrastructure to shrink those five years into five

seconds. By automating the most painful, manual bottlenecks in the development

cycle, we unblock the flow of capital to the front lines of the energy transition. Our

current product delivers agentic AI due diligence for renewable energy

Full-Stack Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT 1

investors. We replace months of manual legal and technical review with a high-

precision AI audit delivered in one hour.

We raised a highly oversubscribed $4M pre-seed round and are backed by

world class investors, including Episode 1, HTGF, PiLabs, Cameron Hepburn 2x

energy unicorn founder), Ian Smedley Barclays Head of Power M&A , Jeremy

Palmer Chairman PhysicsX , and Sam Bourton (ex CTO Quantum Black) amongst

others.

About the founders Daniel, CEO has done over $10 billion in energy M&A transactions both as an

investor at a renewables investment fund in New York and as an advisor at

McKinsey in London and New York. He used to be our ICP, knows the problem

and the industry inside out, has an amazing network in the space, and has earned

his reputation and trust from a decade in the space.

Xander, CTO similarly has led AI risk modeling for over $1 trillion in insured value

of energy assets, working for one of the largest reinsurance companies in the

world SCOR . There, he gained hyper-relevant Agentic AI experience building and

deploying it in production for contract review, a high-stakes environment where

building trust in AI with users is key.

The Role We are looking for an experienced, highly autonomous Full-Stack Engineer to join

us on a contract basis 1 3 months) ASAP, with the possibility to convert into a

full-time role if thereʼs mutual interest.

As an early technical hire, you will work directly with the CTO to build the platform

that powers Veridue's due diligence engine. We need someone comfortable

owning features end-to-end in an early-stage startup environment—moving from

database schema design to frontend implementation with speed and precision.

Example problems you will work on:

Granular Access Controls: Building robust sharing mechanisms and RBAC for

sensitive project data room content.

Full-Stack Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT 2

Human-in-the-Loop AI Workflows: Creating interfaces where users can

review and edit AI-generated outputs, ensuring version history is captured for

training and feedback loops.

Third-Party Data Integration: Integrating external datasets (e.g., UK Land

Registry) and reconciling them with project documents and data room

materials.

The Veridue Mindset

Obsession with the Energy Transition: We are deeply passionate about

solving climate change by removing the massive bottlenecks in energy

infrastructure. We want to use our engineering skills to accelerate the

deployment of abundant, cheap, and clean energy.

Conscious Evolution: We are building an ambitious business, which requires

us to be at our best. We actively invest in our personal growth through

coaching, therapy, meditation, or deep self-reflection, and support each other

in becoming more authentic and grounded.

AI Native Craftsmanship: We don't just build AI; we build with AI. Itʼs our

force multiplier. We are obsessed with staying at the bleeding edge of agents

and are power users of Claude Code. We donʼt ship AI spaghetti; we control

architecture and ship precision-engineered codebases that happen to be built

at 100x speed.

Systems Thinking from First Principles: We strip complex problems down to

their fundamental truths instead of following standard industry playbooks. We

are systems builders who think in architectural primitives rather than just

tickets or features, designing systems that eliminate months of work.

Impact Over Ego: We measure our success by customer ROI and delight, not

just by building intellectually interesting tech. We leave our egos at the door,

handle radical candor gracefully, and lead from a place of vulnerability and

trust.

Relentless Velocity & Extreme Ownership: If someone says a solution will

take a week, our instinct is to figure out how to ship a high-impact MVP in a

Full-Stack Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT 3

day. We don't wait for permission; we see a broken process, take ownership

from concept to success, and put in the focused hours when it matters most.

Ideal Profile

Full-Stack Fluency: Highly proficient with our stack: Python, FastAPI,

PostgreSQL, React, TypeScript, Tailwind, shadcn/ui, TanStack

The Veteran: A deep background in hardcore software engineering, capable

of building secure, scalable web applications.

Data-Heavy Pipelines: Experience building pipelines that extract truth from

messy data or multi-thousand-page PDFs.

Founding DNA Youʼve been a founder, an early hire, or have shipped a side

project from 0 to 1. You don't need a spec to get started.

Reliability Obsessed: Deep familiarity with observability, testing, and ensuring

high-stakes financial/legal data is handled correctly.

What We Offer

Immediate Impact: A 1 3 month high-intensity contract with a clear mission.

Remote or Hybrid: Optional 3 days in office in London with the team,

High-Impact Domain: Energy transition infrastructure is one of the most

consequential investment spaces globally.

Technical Autonomy: You'll own architecture decisions and shape the

technical direction for the features you build.

Convert: possibility to convert into a full-time role if thereʼs mutual interest and

you can do 3 days in office.

Interview Process

Pitch: Send us your website, recent work, or a few bullets on why youʼre a fit.

Intro 15 mins): A quick get-to-know-you with Xander CTO .

Technical Deep Dive 45 mins): A peer-to-peer session focusing on full-stack

systems design and implementation.

Full-Stack Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT 4

Day Zero (paid): Youʼll work on a real problem and ship something. Itʼs the

fastest way to see if our technical gears click.

Full-Stack Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT 5

Full-Stack AI Engineer | Pre- Seed AI & Climate Infra | London / Remote | Contract → FT

Tags

Full-Stack AI Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT

About Veridue AI / the mission we obsess over Energy is the primary lever for the survival of our planet. The transition to a

zero-carbon economy is the greatest challenge of our generation, touching

everything from global affordability to the massive power demands of the AI

revolution.

Our mission is simple: Abundant, cheap, and clean energy for everyone.

To stay within a livable climate threshold, the world must invest $4 trillion every

single year in energy transition infrastructure: renewables, battery storage, and

EV charging. Currently, we are failing to hit that target.

The bottleneck isn't a lack of capital, the cost of hardware, or the speed of

construction. The bottleneck is automatable processes. On average, it takes five

years to get all the paperwork in place to build a one-year construction project.

The world is building paper stacks, instead of solar racks.

We are building the AI infrastructure to shrink those five years into five

seconds. By automating the most painful, manual bottlenecks in the development

Full-Stack AI Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT 1

cycle, we unblock the flow of capital to the front lines of the energy transition. Our

current product delivers agentic AI due diligence for renewable energy

investors. We replace months of manual legal and technical review with a high-

precision AI audit delivered in one hour.

We raised a highly oversubscribed $4M pre-seed round and are backed by

world class investors, including Episode 1, HTGF, PiLabs, Cameron Hepburn 2x

energy unicorn founder), Ian Smedley Barclays Head of Power M&A , Jeremy

Palmer Chairman PhysicsX , and Sam Bourton (ex CTO Quantum Black) amongst

others.

About the founders Daniel, CEO has done over $10 billion in energy M&A transactions both as an

investor at a renewables investment fund in New York and as an advisor at

McKinsey in London and New York. He used to be our ICP, knows the problem

and the industry out, has an amazing network in the space, and has earned his

reputation and trust from a decade in the space.

Xander, CTO similarly has led AI risk modeling for over $1 trillion in insured value

of energy assets, working for one of the largest reinsurance companies in the

world SCOR . There, he gained hyper-relevant Agentic AI experience building and

deploying it in production for contract review, a high-stakes environment where

building trust in AI with users is key.

The Role We are looking for an experienced, highly autonomous Full-Stack AI Engineer to

join us on a contract basis 1 3 months) ASAP, with the possibility to convert into

a full-time role if thereʼs mutual interest.

As a core technical contributor, you will work directly with the CTO to build the

Agentic AI system and platform that powers Veridue's due diligence engine. We

need someone who can bridge the gap between sophisticated AI orchestration

and high-quality product engineering—moving from RAG architecture and agentic

loops to sleek frontend implementation with speed and precision.

Example problems you will work on:

Full-Stack AI Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT 2

Create AI Subagents that tackle high-stakes due diligence pillars like land

rights analysis or permit matrix extraction from thousands of fragmented

documents.

Elevate our Context Engineering through advanced RAG patterns and

knowledge graphs, mapping and extracting truth across 10,000 document

data rooms.

Human–Agent Collaboration: Think Claude Code for Energy Investors.

Building a seamless interface where the AI acts as a digital colleague. Solve

for knowledge access, contextual UI (where users can right-click any content

to start a chat), linking references back to exact UI sections, and incrementally

modifying diligence outputs.

Note: Across any of these projects, you will be working on cutting-edge AI

implementations, but it will be in the real world of production AI, messy data,

and inconsistent criteria. While we have extensive ground-truth data, you will

be responsible for building your own evals to ensure legal-grade precision.

The Veridue Mindset

Obsession with the Energy Transition: We are deeply passionate about

solving climate change by removing the massive bottlenecks in energy

infrastructure. We want to use our engineering skills to accelerate the

deployment of abundant, cheap, and clean energy.

Conscious Evolution: We are building an ambitious business, which requires

us to be at our best. We actively invest in our personal growth through

coaching, therapy, meditation, or deep self-reflection, and support each other

in becoming more authentic and grounded.

AI Native Craftsmanship: We don't just build AI; we build with AI. Itʼs our

force multiplier. We are obsessed with staying at the bleeding edge of agents

and are power users of Claude Code. We donʼt ship AI spaghetti; we control

architecture and ship precision-engineered codebases that happen to be built

at 100x speed.

Systems Thinking from First Principles: We strip complex problems down to

their fundamental truths instead of following standard industry playbooks. We

Full-Stack AI Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT 3

are systems builders who think in architectural primitives rather than just

tickets or features, designing systems that eliminate months of work.

Impact Over Ego: We measure our success by customer ROI and delight, not

just by building intellectually interesting tech. We leave our egos at the door,

handle radical candor gracefully, and lead from a place of vulnerability and

trust.

Relentless Velocity & Extreme Ownership: If someone says a solution will

take a week, our instinct is to figure out how to ship a high-impact MVP in a

day. We don't wait for permission; we see a broken process, take ownership

from concept to success, and put in the focused hours when it matters most.

Ideal Profile

Full-Stack Fluency: Highly proficient with our stack: Python, FastAPI,

PostgreSQL, React, TypeScript, Tailwind, shadcn/ui, TanStack.

AI Orchestration: Experience building custom loops for agentic memory, tool-

use, and state management (beyond simple API wrappers).

Data-Heavy Pipelines: Experience building pipelines that extract truth from

messy data or multi-thousand-page PDFs.

Founding DNA Youʼve been a founder, an early hire, or have shipped a side

project from 0 to 1. You don't need a spec to get started.

Reliability Obsessed: Deep familiarity with observability, testing, and ensuring

high-stakes financial/legal data is handled correctly.

What We Offer

Immediate Impact: A 1 3 month high-intensity contract with a clear mission.

Remote or Hybrid: Optional 3 days in office in London with the team.

High-Impact Domain: Energy transition infrastructure is one of the most

consequential investment spaces globally.

Technical Autonomy: You'll own architecture decisions and shape the

technical direction for the features you build.

Full-Stack AI Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT 4

Convert: Possibility to convert into a full-time role if thereʼs mutual interest and

you can do 3 days in office.

Interview Process

Pitch: Send us your website, recent work, or a few bullets on why youʼre a fit.

Intro 15 mins): A quick get-to-know-you with Xander CTO .

Technical Deep Dive 45 mins): A peer-to-peer session focusing on full-stack

systems design and AI implementation.

Day Zero (paid): Youʼll work on a real problem and ship something. Itʼs the

fastest way to see if our technical gears click.

Full-Stack AI Engineer | Pre-Seed AI & Climate Infra | London / Remote | Contract → FT 5

About Decagon

Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experience. Our AI agents provide intelligent, human-like responses across chat, email, and voice, resolving millions of customer inquiries across every language and at any time.

Since coming out of stealth, Decagon has experienced rapid growth. We partner with industry leaders like Hertz, Eventbrite, Duolingo, Oura, Bilt, Curology, and Samsara to redefine customer experience at scale. We've raised over $200M from Bain Capital Ventures, Accel, a16z, BOND Capital, A*, Elad Gil, and notable angels such as the founders of Box, Airtable, Rippling, Okta, Lattice, and Klaviyo.

We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values—customers are everything, relentless momentum, winner’s mindset, and stronger together—shape how we work and grow as a team.

About the Team

The Research team at Decagon innovates on building the most advanced conversational AI agents for enterprise customers. Decagon’s AI agents understand context, respond with genuine empathy, and solve complex problems with surgical precision.

Our mission is to deliver magical support experiences — AI agents working alongside human agents to help users resolve their issues.

About the Role

On the Research team, you’ll be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. You will design and implement state of the art methods for instruction tuning and information retrieval. We're looking for people with strong engineering skills, writing bug-free

machine learning code, and building the science behind the algorithms that power our AI agents.

Engineers here own their work end-to-end and are trusted to make a real impact. This role is for someone who dives deep into complex system challenges, builds elegant solutions that scale to millions of users, and creates automation that prevents problems before they happen.

In this role, you will

• Develop models for customer support tasks that exceed the performance of closed source models

• Experiment with small open-source models to drive order of magnitude reductions in latency across channels

• Break down ambiguous research ideas into clear, iterative milestones and roadmaps.

Your background looks something like this

• 3+ years of experience in AI/ML engineering or research.

• Proven track record of working on AI/ML projects from concept to production.

• Experience fine-tuning and deploying LLMs in production environments.

• Prior experience working with multi-modal models

Benefits:

• Medical, dental, and vision benefits

• Take what you need vacation policy

• Daily lunches, dinners and snacks in the office to keep you at your best

AI Engineer

• Location: Remote within the UK (London or nearby is a plus)) • Type: Full-time • Salary: £60,000-£70,000 depending on experience

About the role

We’re looking for an AI engineer to build intelligent auto-assessment systems that automate the evaluation of knowledge and skills. Your main focus will be leveraging customer data (marking rubrics and criteria, example marked answers with scores, SME feedback on edge cases, assessment specifications, and historical marking patterns) to deploy auto-assessment solutions that are fast, accurate, consistent, and pedagogically sound. You’ll build APIs, evaluation frameworks, and LLM workflows that help awarding bodies and training providers scale assessment while generating actionable insights for learners and educators.

You’ll own the entire model lifecycle: from data collection and preparation, through experimentation and evaluation, to deployment, observability, and continuous improvement. We’re a small, pragmatic team where processes are informal and everyone pitches in to improve how we work. This role requires strong independence: you’ll own technical decisions, work autonomously without close supervision, and help steer our AI architecture and approach.

About us

sAInaptic is a UK-based AI company reinventing workforce certification. We work with awarding bodies and training providers to automate evaluation of knowledge and skills, helping clients save money and time while improving feedback and consistency of marking. Our vision is to get more skilled professionals into the future workforce.

Key responsibilities

• Leverage customer data (marking rubrics, example marked answers, SME feedback, assessment specifications) to build and deploy auto-assessment solutions that are fast, accurate, consistent, and pedagogically sound

• Design evaluation pipelines and metrics aligned with marking criteria; maintain golden datasets and regression tests; use statistical testing (e.g., t-tests) to rigorously compare model versions and validate improvements

• Experiment with, tune, and benchmark LLMs using tools like DSPy and Langfuse; optimise latency and cost

• Work on multimodal workflows that process images and video alongside text, analysing content and meaning for accurate scoring

• Build systems that generate clear, actionable feedback aligned to assessment criteria, with confidence signals and rationales

• Instrument LLM workflows with tracing and online evaluation; design guardrails and fallbacks (confidence thresholds, human review)

• Help steer technical decisions and architecture for our AI assessment systems • Collaborate with the dev team and assessment experts; participate in code reviews

Requirements

• 5-6 years of ML- or AI-focused engineering experience, OR a PhD in a relevant field (e.g., NLP, machine learning, deep learning, information retrieval, computer vision, or speech processing) with 2+ years of applied industry experience

• Experience owning the full model lifecycle: data collection and preparation, experimentation, deployment, observability, and continuous improvement

• Strong independence: comfortable working autonomously, making technical decisions, and helping steer technical direction without close supervision

• Hands-on experience working with LLMs, agentic workflows, and related frameworks (LangChain, LangGraph, DSPy)

• Strong Python programming skills; experience building APIs • Proven track record designing evaluation frameworks and tuning model

performance, including statistical testing for model comparison (e.g., t-tests to compare error distributions between model versions)

• Experience with experiment tracking and production observability (MLflow/W&B/DVC, Langfuse or similar, confidence calibration, human-in-the-loop)

• Experience with cloud platforms (AWS preferred, or Azure) for model deployment, evaluation, and scalable AI workloads

• Understanding of data privacy, fairness, auditability, system integrity, and scalable architecture

• Proficiency with Git, GitHub, and collaborative development workflows

Nice to have

• Startup experience or experience working in small, fast-moving teams • Experience with assessment technology, EdTech, or automated evaluation systems • Familiarity with ML frameworks (PyTorch, Scikit-learn) • Experience with semantic search, retrieval pipelines, or document analysis • Background in natural language processing or automated scoring • Experience with multimodal AI: speech-to-text for audio/video, computer vision for

images/video, or combining multiple modalities

Benefits

• Equity/stock options

• Pension contributions with employer match up to 5% of salary • Company laptop (MacBook) • 25 days annual leave

Job Title: Senior AI Research Engineer Location: Clerkenwell, London, UK (Hybrid) Department: TFG Labs Reports To: Head of TFG Labs

About TFG Labs: TFG Labs is the innovation arm of Twenty First Group, dedicated to pioneering AI-driven solutions that redefine the future of sports. We focus on developing groundbreaking technologies that enhance decision-making, performance analysis, and fan engagement across the sports industry. As a senior member of the Labs team, the research experiments you conduct will shape how the future of how AI and sports intersect.

Role Overview: We are seeking a visionary and experienced Senior AI Engineer with a growth mindset to be a foundational pillar of our new AI Engineering team in TFG Labs. This is a role for a strategic thinker and a hands-on builder who is obsessed with the rapid advancements in AI. You will be our go-to expert on emerging AI paradigms, from agentic workflows to multi-modal systems, and will be empowered to drive our R&D roadmap. Your primary mission is to architect and prototype the next generation of AI-powered tools that will give TFG and our clients a definitive competitive edge, on and off the pitch.

Key Responsibilities:

● Lead AI Research & Development: Drive the R&D of emerging technologies, and move beyond hype to identify tangible value for our business and clients.

● Architect and Build Advanced Prototypes: Lead the hands-on development of sophisticated AI prototypes, particularly focusing on agentic systems, automation platforms, and novel applications of Large Language Models (LLMs).

● Drive Technical Adoption: Analyse and drive the evolution and internal adoption of our AI infrastructure and tooling.

● Thought Leadership & Evangelism: Act as a thought leader within TFG. Translate complex AI concepts and the implications of your experiments for diverse audiences, from junior engineers to the C-suite. Mentor other team members, fostering a culture of curiosity and excellence.

● Defining Pathways for Integration: Collaborate with cross-functional product and engineering teams to chart a path for successful prototypes to become scalable, integrated solutions within our core products.

Core Qualifications:

● Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

● 5+ years of hands-on experience in a dedicated AI/ML engineering role, with a demonstrable track record of building and shipping complex systems.

● Expert-level proficiency in Python and its core AI/ML libraries (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex), and comfortable transitioning to a ‘pilot’ role using AI tools to amplify your productivity.

● Proven experience designing, deploying, and managing scalable AI solutions on at least one major cloud platform (AWS, GCP, Azure).

● Solid understanding of MLOps principles and experience with relevant tools (e.g., Docker, Kubernetes, MLflow) for building robust, production-ready systems.

The Ideal Candidate Profile: This role is a perfect fit if you...

● Are at the bleeding edge of AI: You don't just follow the news; you're ahead of it. You actively follow research from top labs (OpenAI, DeepMind, Anthropic), experiment with open-source models the week they drop, and can articulate the architectural nuances between them.

● Are an architect of intelligent agents: You have hands-on experience designing and building agentic AI systems. You understand how to orchestrate multiple models, tools, and memory to perform complex tasks and are familiar with architectures like the Model-Control-Perception (MCP) loop or similar multi-agent frameworks.

● Are a master of the modern AI toolkit: You were an early adopter of GitHub Copilot and have since graduated to tools like Cursor or building your own custom developer automation. You intuitively use AI to achieve a 10x developer workflow and can evaluate new tools for team-wide adoption.

● Are a clear communicator and educator: You can demystify complex AI concepts. You can confidently explain to a non-technical stakeholder why an LLM hallucinates or why "2+2" might not always equal "4" in a probabilistic model, tailoring your explanation to the audience.

● Are passionate about the application: You have a genuine interest in sports. You understand that our clients' businesses run not just on data, but on a deep-seated passion for the game. Creative taste is a significant bonus.

What We Offer:

● A pivotal role in shaping the AI strategy of a leader in the sports intelligence industry. ● Significant autonomy and the budget to explore bold ideas and cutting-edge

technologies. ● The opportunity to work on genuinely novel problems with a world-class,

collaborative team. ● Competitive salary, comprehensive benefits package. ● A flexible hybrid working model and a healthy dose of sports-related fun.

Application Process: Interested candidates should submit their resume and a cover letter. In your cover letter, please briefly describe a recent AI experiment you've run (personal or professional) or a research paper that has recently excited you and why.