Software Engineer Analysis Software in London

About ExTrac

ExTrac is a decision intelligence company used by governments, defence organisations, financial institutions, and corporates operating in complex, fast-moving environments. Our capabilities fuse curated data sources, domain-specific AI, and deep human expertise to transform information overload into clear, actionable foresight. Our ambition is to become the analytical backbone that organisations rely on when geopolitical uncertainty becomes an opportunity or a strategic risk.

We are looking for a Software Engineer to join ExTrac's AI team, building Co-Analyst and the analytical AI features around it. Co-Analyst is a user-facing multi-agent system that works alongside intelligence analysts to research and write reports. A planning loop decomposes an analyst's question, fans work out to sub-agents, and assembles the results into a report where every claim traces back to the chunk of source it came from. Underneath sits hybrid retrieval over a large unstructured corpus: analyst intent translated into structured filters, combined with keyword and dense vector search, across multiple languages and media types.

In a single quarter the work spans agent orchestration, retrieval, graph analytics, and long-running streaming pipelines, alongside the services and databases underneath them. You will own well-defined features and components end to end across a Python and Go codebase, working alongside senior engineers who set technical direction, the data team who own the ingestion pipelines, and a research-focused ML team who train and evaluate the models we integrate and serve. The loop is short: product brings an idea, often recent and unproven, and our job is to spike an implementation and take it to a production feature. This hire exists to add capacity on the AI team's hard problems: an engineer who can independently deliver well-scoped features and components, and who is building towards owning more of the system end to end.

Agentic and analytical AI features

• Build and improve components of the agent loop itself: context assembly, tool selection, and sub-agent orchestration, with guidance from senior engineers on the team.
• Build the analytical AI features that sit alongside it, from network construction through to the summaries analysts read.
• Help prove that changes are improvements, running experiments against live analyst traffic behind feature flags.
• The same vectors drive network construction and community detection.
• Work within a model-agnostic design, swapping models and embeddings on the back of the ML team's evaluations rather than being locked to one.
• Take a well-defined problem, clarify requirements with your lead or a senior engineer, and ship it to production with regular check-ins rather than close oversight.
• Work with the storage layer as a design concern rather than an implementation detail: schema, indexing strategy, and access patterns, across relational, document, and vector stores.
• Build and operate supporting services across Python and Go, with growing ownership of design, deployment, and operations as you build track record.
• Help hold agent workflows to production standards for latency, cost, and reliability, in a system where non-determinism is a given.

Working with analysts, product, and the ML team

• Partner with the ML team on agentic approaches, helping take proven concepts to production and working through the engineering, performance, and reliability problems a research implementation does not have to.
• Help integrate and serve the models they train, and contribute to the production infrastructure their evaluation frameworks run on.
• You will spend more of your time in Python and Go services, databases, and APIs than in a prompt file, and you know the difference between something that demos well and something that holds up under production load, latency, and cost.
• Experience with them is useful, but we build most of our own orchestration, because off-the-shelf abstractions have not survived our requirements around evaluation, control, and production performance.
• You can take a recent technique or paper, help spike an implementation, and reason clearly about whether it is worth taking further.
• Our software sits underneath decisions taken by governments, defence organisations, and institutions operating where being wrong or late carries real consequences.
• Strong performance means owning larger features and whole services end to end, writing the technical designs others build on, and leading reviews rather than only taking part in them.
• There are established patterns for running web services and for training models. You will be helping work those out, and that experience is still rare.
• Making our systems work inside FedRAMP environments is a major upcoming project, and engineering under that kind of constraint is a skill set that stays with you.

Due to the nature of our work and the clients we support, applicants must be eligible to obtain UK security clearance.

Requirements

• 2+ years of professional software engineering experience, with demonstrated ability to build and ship production-grade services with solid test coverage, and experience owning features or components end to end within a larger system.
• Proficiency in building services in Python, with working knowledge of Go or the ability to pick it up quickly.
• A good understanding of distributed systems and databases, including writing asynchronous code that performs under load.
• Comfortable working with trunk-based deployment.
• You communicate clearly in writing and can produce documentation colleagues can follow, and you look for a way through rather than concluding something cannot be done.
• Breadth and curiosity across the stack: an interest in deployment pipelines, database behaviour, security and AI guardrails, and in validating analytical outputs and feeding analyst feedback into requirements.
• Experience with retrieval systems and large-scale vector database performance (Elastic).
• Experience with graph or network analysis at scale.
• Experience building retrieval or analysis that works across multiple languages.
• Experience operating multi-tenant systems where data isolation is a hard requirement.
• A significant upcoming project is making our systems work within FedRAMP environments.

Benefits

• Competitive salary based on skills and experience.
• A generous benefits package, including Private Medical Health Insurance and enhanced pension contributions.
• Enhanced parental leave and a workplace nursery scheme.
• 33 days of leave across the year inclusive of bank holidays.
• Flexible working. The team is typically in our central London office two days a week, and you are welcome to come in up to five.

ExTrac AI provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, colour, religion, sex, national origin, age, disability, genetic information, sexual orientation, gender identity, or gender expression. ExTrac AI is committed to a fair and transparent hiring process. Please be advised that we may use artificial intelligence-driven tools to assist our recruitment team in screening, assessing, and selecting candidates for this position but all hiring decisions will be made by a member of our team.