Senior Software Engineer - AI Foundations
AI in this role
Help us use technology to make a big green dent in the universe!
Kraken powers some of the most innovative global developments in energy.
We create the technology that redefines utilities and unlocks a new energy system of the future. By optimising renewable generation, building a more intelligent grid, and empowering utilities to deliver an exceptional customer experience, our operating system is transforming the industry worldwide.
It’s an incredibly exciting time to work in energy. Join us on our mission to improve the lives of ONE BILLION humans within the decade and shape a cleaner, better future for everyone.
AI is a key investment area for Kraken Technologies. A crucial part of this is building the shared foundations that let every team use AI well and move faster on our mission.
You'll work in AI Foundations. We build the platform that lets teams across Kraken build and run AI agents. Our work covers four areas:
Access: connecting people and systems to approved AI models and tools
Context: grounding AI in trusted Kraken knowledge, data and systems
Enablement: reusable building blocks for AI-powered workflows and products
Governance: permissions, safety, quality, cost and visibility across the lifecycle
🏡 Where you'll fit in
We're hiring Senior Software Engineers to join one of our three squads:
Context: Build the Kraken-specific knowledge layer to make LLMs useful. This covers our internal AI assistant, a structured "client brain" that captures client context and decisions, and pipelines that collect knowledge from tools like Notion, Slack and GitHub.
Tooling: deliver LLMs into people's hands. We run the AI Hub (usage insights, MCP gateway, self-serve and specialist agents), the LiteLLM gateway behind Claude Code, Codex and Claude Desktop, and secure cloud dev boxes for AI-assisted engineering.
Evals & Observability: covers skill evals, internal benchmarking, agent safety and guardrails, and observability for live AI runs.
Squads are flexible: when priorities shift, people move. This is a hands-on senior individual-contributor role. With your squad lead and the wider team, you'll own large parts of our platform, turn ideas into production systems, shape architecture decisions and help raise the engineering bar.
👾 What you'll own
Build shared AI platform services: Design, build and run Python services that other teams rely on, such as gateways, agent runtimes, knowledge pipelines and eval harnesses.
Build and run agents: Work out how agents are triggered, authenticated, monitored and governed across systems like Slack, GitHub, Notion and Asana. Ship both self-serve agents and specialist agents.
Ground AI in Kraken context: Collect, structure and serve company knowledge so agents give answers that are correct, current and safe to use.
Measure and prove quality: Define meaningful test cases, build evals whose results can be reproduced, and add tracing so we know how AI behaves in real use.
Build in safety and governance: Turn permissions, guardrails, budgets and data-access rules into software you can maintain, working with Security and TechOps.
Operate in AWS: Deploy and support services on AWS and Kubernetes, and make sound reliability, performance and cost trade-offs.
Drive adoption: Work directly with engineers and non-technical teams, run workshops, write clear docs and turn feedback into product.
Raise the engineering bar: Review designs and code, mentor others, and create patterns that can be reused across AI Foundations.
🧠 What you bring to the party
Strong senior-level software engineering: You have owned complex services end to end, from design through testing, deployment and operation.
Deep engineering fundamentals: Good judgement on system design, concurrency, security, testing and architecture trade-offs. Strong production Python.
Hands-on LLM and agent experience: You have built real things with LLMs, you know where they fail, and you use AI coding tools every day.
Cloud experience: You're comfortable running services in AWS and owning their reliability and scalability.
Product sense: You care whether people actually use what you build.
Clear communication: You can explain trade-offs to technical and non-technical people and challenge ideas constructively.
Learning agility: You pick up new tools and domains quickly in a field that changes every month.
🚀 What success looks like
Adoption: You ship platform features that teams across Kraken adopt and rely on.
Solid systems: The services you own are observable, secure, scalable and cost-aware.
Trust at scale: Teams can build and trust agents without rebuilding the basics.
Team impact: You make your squad, and the teams around it, better.
⭐️ Bonus points:
AI engineering: Pydantic AI, LiteLLM, LangChain, MCP servers
Knowledge and retrieval: RAG, search, embeddings, knowledge graphs
Evals and safety: Inspect AI, Ragas, OpenAI Evals, NeMo Guardrails, red teaming
Platform: Kubernetes, sandboxed or cloud dev environments, AWS Bedrock
Backend: Django
Observability: Datadog, OpenTelemetry
Are you ready for a career with us? We want to ensure you have the right tools and environment to unleash your potential. If you have any accommodation requests, please contact us at inclusion@kraken.tech. We’ll do our best to tailor the experience to your needs so you can feel comfortable, confident and be at your best!
Studies have shown that some groups of people, like women, are less likely to apply to a role unless they meet 100% of the job requirements. Whoever you are, if you like one of our jobs, we encourage you to apply as you might just be the candidate we’re looking for! At Kraken, we're creating a team of genuine, honest, empathetic people. Our people are our strongest asset and the unique skills and perspectives people bring to the team are the driving force of our success. As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. We consider all applicants without regard to race, colour, religion, national origin, age, sex, gender identity or expression, sexual orientation, marital or veteran status, disability, or any other legally protected status.
*Our (i) Applicant and Candidate Privacy Notice and Artificial Intelligence (AI) Notice, (ii) Website Privacy Notice and (iii) Cookie Notice govern the collection and use of your personal data in connection with your application and use of our website. These policies explain how we handle your data and outline your rights under applicable laws, including, but not limited to, the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Depending on your location, you may have the right to access, correct, or delete your information, object to processing, or withdraw consent. By applying, you acknowledge that you’ve read, understood and consent to these terms
Please note that, in line with our current recruitment policy, we are unable to offer visa sponsorship for this position; applicants must have the right to work in the country that they're applying to, at the time of application.*
How we rate this
Senior Software Engineer - AI Foundations at Kraken Technologies rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What are the limits of OpenAI that you've run into, and how did you work around them?
- What's a project where you used Claude hands-on?
- Walk me through how you've used LangChain in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI Agents, OpenAI, Claude, and LangChain. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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