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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and operating agentic systems and production-grade services, with a strong focus on Python and Go development, cloud infrastructure, and effective collaboration with cross-functional teams. Proficient in designing APIs, managing unstructured datasets, and ensuring system reliability and performance.
Highest-signal resume keywords
Python DevelopmentGo ProgrammingAgentic Systems EngineeringCloud Infrastructure ManagementDistributed Systems Design
ATS Keywords
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Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringAsynchronous Code DevelopmentFeature Flag ImplementationTechnical Design DocumentationPerformance ProfilingDatabase ManagementAPI DesignModel IntegrationStreaming Pipeline DevelopmentTest Coverage Implementation
Soft Skills
Strong CommunicationCollaboration SkillsUser Feedback IntegrationProblem-SolvingAdaptability
Tools & Technologies
CI/CD PipelinesInfrastructure as CodeRelational DatabasesDocument StoresVector Stores
Certifications & Qualifications
UK Security Clearance Eligibility
Industry Keywords
Agent LoopsAnalytical AI FeaturesNetwork ConstructionCommunity DetectionProduction InfrastructureAI GuardrailsDeployment Pipelines
Tech Stack
Tools & technologiesAssemblyCloudDistributed SystemsPythonGo
About the role
Key responsibilities & impact- Build and improve agent loops, including context assembly, tool selection, and sub-agent orchestration
- Build analytical AI features from network construction through analyst-facing summaries
- Run experiments against live analyst traffic behind feature flags
- Define improvement criteria and assess whether approaches should be advanced or discontinued
- Develop approaches for unstructured, imperfect datasets
- Use embeddings for retrieval, network construction, and community detection
- Maintain model-agnostic designs and integrate models and embeddings selected through ML evaluations
- Gather requirements, write technical designs, and ship production features with minimal oversight
- Own services end to end, including consolidation or decommissioning of replaced services
- Design APIs for internal teams and customers with clear contracts and versioning
- Design schemas, indexing strategies, and access patterns across relational, document, and vector stores
- Contribute to and lead system design and architecture decisions
- Design, build, deploy, and operate Python and Go services
- Ensure agent workflows meet production standards for latency, cost, and reliability
- Build and operate long-running streaming pipelines with caching and recovery capabilities
- Work directly with analysts to turn user feedback into system changes
- Iterate on product requests and identify conflicts with longer-term capability work
- Partner with the ML team to productionize agentic approaches and solve engineering, performance, and reliability challenges
- Integrate and serve trained models and build production infrastructure for evaluation frameworks
Requirements
What you’ll need- Applicants must be eligible to obtain UK security clearance
- Applicants must be nationals of a NATO member state, Australia, or New Zealand
- 4+ years of professional software engineering experience
- Demonstrated ability to stand up production-grade services with comprehensive test coverage and own features end to end
- Proficiency in Python and working knowledge of Go or ability to pick it up quickly
- Experience building and operating agentic systems, LLM applications, or production retrieval used by real users
- Solid understanding of distributed systems, databases, and software engineering patterns
- Experience writing performant asynchronous code that scales under real workloads
- Experience with cloud infrastructure, infrastructure as code, and CI/CD pipelines
- Experience with feature flags and trunk-based deployment
- Ability to diagnose and fix issues such as memory leaks through profiling
- Ability to scope technical designs from PRDs and challenge approaches that do not hold up
- Strong communication and collaboration skills
- Ability to write clear technical documentation and discuss requirements with engineering and wider teams
- Breadth across deployment pipelines, database behaviour, security, and AI guardrails
- Ability to quickly learn unfamiliar tools
- Interest in validating analytical outputs and incorporating analyst feedback into requirements discussions
Benefits
Comp & perks- Competitive salary based on skills and experience
- Private Medical Health Insurance
- Enhanced pension contributions
- Enhanced parental leave
- Workplace nursery scheme
- £500/year education budget
- More expensive education items, such as conferences, covered with manager approval
- 33 days of leave across the year inclusive of bank holidays
- Flexible working
- Team typically works in the central London office two days a week, with the option to come in up to five days