Associate Director, Software Engineering (GenAI Agent Platform)

Job description

Partner with cross-functional teams to define, build and roll out a scalable Generative AI agent platform for priority banking use cases from pilot to production.

Own the end-to-end platform engineering

design and implement the agent runtime, orchestration, tool/function calling, prompt and workflow management, memory/state handling, and integration patterns—leveraging frameworks such as LangChain/LangGraph (where appropriate) while avoiding unnecessary vendor/framework lock-in. Establish platform reliability and quality by building in evaluation and testing (offline/online), guardrails, observability (logs/traces/metrics), and clear SLOs/SLAs to ensure accuracy, Continuously monitor and optimise platform performance in production, including model selection, prompt/agent tuning, retrieval quality, caching, throughput, and resilience; drive root-cause analysis and preventative improvements.

Embed security, privacy and compliance by design: ensure controls for data handling, access management, encryption, auditability, model risk considerations, and safe tool use; align to internal governance and relevant regulatory expectations.

Provide technical leadership and hands-on support

troubleshoot complex issues, support onboarding of delivery teams, create runbooks, and act as an escalation point for incidents and production support.

Maintain strong platform documentation and enablement

publish reference architectures, APIs/SDKs, templates, best practices, and developer guidance to accelerate adoption and consistent delivery across teams. Track and evaluate emerging GenAI/agent capabilities (e.g., new orchestration patterns, evaluation methods, safety techniques, model/tooling advances) and translate them into pragmatic platform enhancements with clear value, risk and cost trade-offs.

Education & English

Bachelor's degree or above in Computer Science/Engineering (or related); Good verbal communication in English.

Software Engineering

3+ years' hand-on coding practice, strong Python or Java or Golang, with usage of at least one major cloud (AWS/Azure/GCP); ability to deploy and operate services in production (Docker/Kubernetes preferred).

GenAI / LLM Delivery

1+ years building and shipping LLM/GenAI applications; knowledge with agentic workflows and tool/function calling (multi-agent systems a plus). SME in at least one area (Performance Monitoring, Agent Governance Control, Agent Identity, Harness, Agent SDK, Agent Policy / Guardrail) Be able to demonstrate a strong vision for the future of agent platforms. Be able to articulate concrete best practices for creating skills, agents, or MCP tooling.

Problem-solving & commitment, strong ability to develop creative solutions to complex challenges, working effectively with technical and non-technical stakeholders. Demonstrates an AI-native mindset by applying AI-driven approaches, including coding assistants, to improve productivity, quality, and engineering best practices.

RAG/MCP preferred

Practical RAG experience (retrieval, chunking, embeddings, vector databases such as Milvus/FAISS/Elastic/Pinecone)