Agentic AI Analyst

Role Description

• Responsible for building production-ready backend services for agentic workflow components aligned to solution architecture and platform standards.
• Implement solution designs by building Python services, worker processes, and reusable libraries following defined architecture, patterns, and standards.
• Develop agentic workflow components: tool connectors, orchestration steps, state management modules, retrieval components, and approval/escalation flows.
• Build reliable LLM interaction layers: tool/function calling, schema-validated structured outputs, guardrails, safe tool execution boundaries, and fallback behaviors.
• Implement robust backend patterns: async execution, job queues,retries/idempotency, compensating actions, and failure isolation for long-running workflows.
• Deliver production readiness: logging/tracing, metrics, decision logs, run replay support, performance profiling, and cost/latency controls.
• Write clean, maintainable, testable code with strong review discipline:unit/integration tests and regression testing for prompts/agents where applicable.
• Collaborate closely with the Agentic AI Architect and technical leads; support delivery across DEV/UAT/PROD including defect triage and operational support.

• The role supports one of our top-tier banking clients in London (Canary Wharf) and requires a minimum of three days on-site presence.
• This is a permanent position based in the UK. We will only consider applicants whoare eligible to work in the UK. For this role do NOT offer visa sponsorship.

• 4+ years in Python backend development, including building production
  
  APIs/services and/or worker-based processing systems.
• Demonstrable experience in implementing Generative AI, AI/LLM-enabled featuresor systems (agentic workflows, RAG, tool calling, evaluation/monitoring) is preferred.
• Strong capability in backend fundamentals: service boundaries, API contracts, asyncexecution, retries/idempotency, error handling, and performance optimization.
• Advanced Python engineering skills: clean architecture, modularity, testability,packaging, secure coding, and maintainability at team scale.
• Strong experience building API-first services (FastAPI or equivalent), RESTFul APIsincluding auth patterns (OAuth2/JWT/API keys), versioning, and backwards compatibility.
• Integrate and manage relational and vector databases.
• Strong schema/data contract practice using typed models and validation (e.g.,Pydantic-style patterns), including strict structured outputs and schema evolution.
• Working with version control tools like Git Hub (branching, PR reviews, release tagging, CI-friendly workflows).
• Strong experience with context grounding methods, and context engineering when working with LLMs (RAG, evidence capture, context selection, prompt/context structuring).
• Experience using automation tools and integrating with external applications (API-based integrations, workflow triggers/actions, third-party systems).
• Experience building integration-heavy systems: consuming/producing APIs, handling enterprise data formats, and creating maintainable connectors.
• Working knowledge of distributed execution patterns: background jobs, scheduling,worker pools, and stateful workflows.
• Ability to work with ambiguity, break down requirements, and deliver reliably with strong ownership and communication.

• Experience with agent orchestration frameworks (e.g., Lang Graph-like patterns) andLLM observability/evaluation tools (Langfuse-like capabilities).
• Experience integrating enterprise-hosted LLMs (including vertex AI / managed equivalents) and working with provider-agnostic abstraction layers (routing, fallback,cost-aware selection).
• Experience with job queues, distributed tracing, dashboards/alerts, and runbook-driven operational practices.
• Experience supporting regulated enterprise delivery: audit-friendly logging, change controls, secure configuration, and controlled deployments.
• Platform/Dev Ops awareness (preference):
  Docker basics;
  Kubernetes/Open Shift fundamentals; logging/monitoring patterns; secrets management and environment separation (DEV/UAT/PROD).