Description
We are currently seeking an experienced professional to join our team in the role of Associate Director, Software Engineering.
Principal Responsibilities
- Design, build, and ship production-quality services in line with technology standards, governance, and business controls.
- Assist with the design, iteration, and optimisation of prompts for a wide range of LLM use cases,instruction following, structured output generation, classification, summarisation, code generation, and reasoning tasks.
- Build and manage prompt libraries and versioning strategies, treating prompts as first-class engineering artefacts.
- Collaborate with product and domain teams to translate business requirements into precise, well-structured prompt specifications.
Agentic AI & LLM Integration
- Support and drive the implementation, and maintenance of agentic systems,autonomous agents, multi-agent pipelines, tool-use workflows, planning loops, and memory-augmented reasoning.
- Implement LLM observability (logging, tracing, evaluation pipelines, and guardrails) to maintain quality and reliability in production AI systems.
- Advise on responsible AI deployment, including output validation, human-in-the-loop design, and risk mitigation for agentic workflows.
Team Leadership, Product/Agile Partnership & Global Engagement
- Serve as part of the local team engineering leadership, helping set direction, priorities, and delivery standards for the engineering pods within Fincrime Investigations value stream.
- Partner closely with Product Management to clarify value, scope, and success measures; contribute to discovery, solution options, and delivery plans.
- Work day-to-day with agile delivery partners (e.g., Scrum Masters/Delivery Leads) to maintain a healthy delivery cadence, manage dependencies, and ensure transparent reporting of progress, risks, and blockers.
Requirements
- Full-Stack Engineering
+ Strong proficiency in Java / Spring Boot,REST APIs, event-driven services, security, and performance optimisation. + Solid React development skills and API integration. + Experience with relational and in-memory databases (PostgreSQL, Redis). + Messaging and streaming platforms,Kafka (or equivalent).
- Prompt Engineering
+ Demonstrable, hands-on experience engineering prompts for production LLM applications (not just prototypes). + Understanding of tokenisation, context limits, temperature tuning, and model-specific behaviours across major LLM providers. + Experience structuring prompts for tool/function calling, structured JSON output, and multi-turn conversations.
- DevOps & Infrastructure
+ Kubernetes,deployments, services, ingress, Helm, Kustomize, HPA, and RBAC. + CI/CD pipelines,GitHub Actions, Jenkins, or equivalent. + Infrastructure as code,Terraform. + Cloud platforms,AWS, AliCloud, GCP, or Azure.