We are seeking an experienced Senior AI Software Engineer to support an enterprise AI initiative from use-case discovery through production implementation. The role combines strong Python and Java engineering with hands-on experience building secure, scalable AI, Generative AI, and agentic solutions. The successful candidate will work onshore with business, product, architecture, data, security, and engineering teams to deliver measurable outcomes in a regulated banking environment.
Key Responsibilities
- Design, build, test, deploy, and support AI-enabled enterprise applications using Python and Java.
- Develop Generative AI solutions, including conversational assistants, retrieval-augmented generation pipelines, enterprise search, summarization, and workflow automation.
- Build agentic capabilities using tool or function calling, orchestration, guardrails, human-in-the-loop controls, and auditable execution flows.
- Integrate large language models, machine learning models, APIs, vector stores, enterprise data sources, and existing applications.
- Develop robust REST APIs and microservices using modern Python and Java frameworks.
- Implement prompt engineering, document chunking, embeddings, retrieval, reranking, grounded response generation, and output validation.
- Create evaluation frameworks for accuracy, groundedness, safety, latency, reliability, and cost; automate regression testing for AI behaviour.
- Implement MLOps and LLMOps practices, including version control, CI/CD, containerization, model and prompt versioning, monitoring, and incident support.
- Apply privacy, security, identity and access management, responsible AI, and model-risk controls appropriate to a regulated environment.
- Partner with stakeholders to clarify use cases, assess feasibility, define acceptance criteria, demonstrate prototypes, and transition solutions into production.
- Perform code reviews, troubleshoot complex issues, document technical decisions, and mentor engineering team members.
Preferred Qualifications
- Experience with Azure AI services, Azure OpenAI, Azure AI Search, or comparable cloud AI platforms.
- Experience with frameworks such as LangChain, Semantic Kernel, LlamaIndex, PyTorch, TensorFlow, or scikit-learn.
- Knowledge of agentic AI patterns, model context protocols, multi-agent orchestration, and enterprise knowledge platforms.
- Experience implementing AI governance, responsible AI controls, privacy safeguards, content safety, and model-risk documentation.
- Financial services or banking domain experience, including familiarity with security, audit, compliance, and data-governance expectations.
- Experience working in Agile delivery environments and using AI-assisted development tools such as GitHub Copilot
