- Build AI-enabled features that generate client summaries from structured and unstructured data using OpenAI APIs and similar LLM providers.
- Integrate LLM calls into application services - prompt construction, model selection, structured outputs (JSON), streaming responses, token-budget and cost management, retries, and error handling.
- Assemble context for the model - retrieve and shape data from databases and internal APIs into the structured input the model needs to produce each summary type.
- Design and iterate on prompts and templates for different summary "types," and build lightweight evaluation to check accuracy, completeness, and faithfulness (no hallucinated facts).
- Expose capabilities through clean backend APIs so other teams can consume them.
- Apply responsible-AI guardrails - PII handling/redaction, prompt-injection defenses, output validation, and audit logging suitable for a regulated environment.
- Collaborate with engineering, business analysts, and compliance stakeholders to define what a "good" summary looks like and to validate outputs.
- Use AI coding assistants (e.g., GitHub Copilot, ChatGPT) to accelerate your own development.
Required Qualifications (Must Have)
- 3-5 years of professional software development experience as a hands-on developer (junior to mid-level).
- 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).
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