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Kraken Technologies

Cloud-based DERMS enabling real-time energy trading

Senior Software Engineer - AI Foundations

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • You have owned complex services end to end, from design through testing, deployment and operation.
  • You have good judgment on system design, concurrency, security, testing and architecture trade-offs, and strong production Python skills.
  • You have built real things with large language models, understand where they fail, and use AI coding tools every day.
  • You are comfortable running services in AWS and owning their reliability and scalability.
  • You care whether people actually use what you build.
  • You can explain trade-offs to technical and non-technical people and challenge ideas constructively.
  • You pick up new tools and domains quickly in a rapidly changing field.

Responsibilities

  • Design, build and run Python services that other teams rely on, such as gateways, agent runtimes, knowledge pipelines and evaluation harnesses.
  • Determine how agents are triggered, authenticated, monitored and governed across systems such as Slack, GitHub, Notion and Asana, and ship self-serve and specialist agents.
  • Collect, structure and serve company knowledge so agents provide answers that are correct, current and safe to use.
  • Define meaningful test cases, build evaluations with reproducible results, and add tracing to understand AI behavior in real use.
  • Implement permissions, guardrails, budgets and data-access rules as maintainable software, working with Security and TechOps.
  • Deploy and support services on AWS and Kubernetes, making reliability, performance and cost trade-offs.
  • Work directly with engineers and non-technical teams, run workshops, write clear documentation and turn feedback into product.
  • Review designs and code, mentor others, and create reusable patterns across AI Foundations.

Desired Qualifications

  • Pydantic AI, LiteLLM, LangChain or MCP servers.
  • Retrieval-augmented generation, search, embeddings or knowledge graphs.
  • Inspect AI, Ragas, OpenAI Evals, NeMo Guardrails or red teaming.
  • Kubernetes, sandboxed or cloud development environments, or AWS Bedrock.
  • Django.
  • Datadog or OpenTelemetry.

About the Company

Kraken Technologies

Cloud-based DERMS enabling real-time energy trading

KrakenFlex provides a cloud-based DERMS that lets asset owners, energy traders, and retailers monitor and control distributed energy resources in real time. It connects to a wide range of DERs—from storage and generation facilities to residential devices and electric vehicles—and optimizes their output to participate in ancillary and wholesale markets. The product is offered as software-as-a-service (SaaS) with subscription fees (and possibly transaction-based fees for market activities) and is designed for sub-second response times with comprehensive monitoring. Its goal is to help clients maximize value from their energy assets by coordinating DERs across multiple markets from a single platform.

Company size
1,001-5,000
Company stage
Early VC
Total funding
$1B
Headquarters
London, United Kingdom
Founded
2014

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