Description

Job Description -

Required Qualifications (Must Have)

Strong proficiency in at least one backend language - Java (with Spring Boot) and/or Python (FastAPI / Flask). We are open to either.

Hands-on experience calling LLM APIs - particularly the OpenAI API (chat completions, function/tool calling, structured/JSON outputs, embeddings) - or a strong willingness and demonstrated aptitude to ramp up quickly.

Practical prompt-engineering skills - writing, testing, and iterating on prompts to get reliable, well-structured output.

Experience integrating with data sources - relational databases (SQL) and REST APIs.

Solid understanding of RESTful API design and JSON.

Good engineering fundamentals - version control (Git), testing, and writing maintainable code.

Awareness of data privacy / PII concerns and a careful, quality-focused mindset.

Strong problem-solving and communication skills; able to work with non-technical stakeholders to shape requirements.

Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience).

Familiarity / Nice to Have (any subset is a plus)

LLM / orchestration libraries - Spring AI, LangChain / LangChain4j, LlamaIndex, Semantic Kernel, or equivalent.

Other LLM providers - Anthropic Claude, Google Gemini, or open-source models (Llama, Mistral).

Streaming responses (SSE / WebSockets) and async patterns for LLM output.

Evaluation tooling for LLM outputs - measuring faithfulness, hallucination, and task success; familiarity with Langfuse / LangSmith or similar observability for AI.

Cloud experience (Azure / AWS / GCP) and containerization (Docker).

CI/CD (Jenkins or similar) and build tooling (Gradle / Maven for Java, or pip/poetry for Python).

Responsible-AI / model-governance practices in a regulated context.

Exposure to financial-services, AML/KYC, compliance, or risk domains

Key Skills

Education

Any Graduate