AI Developer

Application Design

• Translate team requirements into complete AI service designs.
• Select and integrate the most appropriate LLMs, vision, or audio models (OpenAI, Gemini, Claude, CoPilot, etc.) for each use-case.
• Build intuitive HTML interfaces to make the tools easy to access and easy to use.

Agent Architecture

• Help map user journeys and business processes to pinpoint high-value agent opportunities.
• Design composable pipelines using frameworks such as LangGraph, AutoGen, or CrewAI to orchestrate agent societies and tool calls.

Agent Development and Prompt Engineering

• Chain LLM-driven agents and assist with fine-tuning or retrieval-augmented generation (RAG) when needed.
• Craft reusable, version-controlled prompt libraries; implement evaluation testing for latency, hallucination, and bias.
• Leverage APIs and protocols (MCP) to extend and integrate advanced functionality.

Data and Tool Integrations

• Ingest, clean, and transform structured and unstructured data (text, images, video) for agent consumption.

MLOps and Observability

• Track latency, cost, and quality; tune prompts/embeddings iteratively.
• Maintain dashboards for real-time health metrics and experiment management.

Cross-Functional Collaboration

• Partner with Product, Design, and Domain SMEs to translate business needs into agent specs.
• Deliver SDKs, docs, and “prompt playbooks” enabling non-technical colleagues to extend agents.

Thought Leadership

• Stay current on GPT-4o, Gemini Ultra, open-weight SLMs, ReAct, Reflexion, Voyager, etc.
• Share insights via demos, brown-bags, and internal blogs; recommend pilots for emerging capabilities.

Qualifications: 

Education

• Bachelor’s in Computer Science, Data/AI Engineering, Computational Linguistics, or related field (Master’s a plus) or equivalent work experience.

Experience

• 2–4 years building production LLM or conversational-AI solutions, including at least 1 year with agent orchestration frameworks.

Technical Skills

• Proficient in Python; familiarity with TypeScript/Node is a plus.
• Hands-on with LLM APIs (OpenAI, Gemini, Azure OpenAI, open-source SLMs).
• Solid grasp of embeddings, vector search, RAG patterns, and prompt-engineering best practices.
• Working knowledge of cloud platforms and CI/CD pipelines.

Soft Skills

• Systems thinker with user-centered focus.
• Clear communicator able to translate technical complexity.
• Organized, resourceful, and comfortable juggling fast-moving projects.

Bonus

• Multimodal model experience (vision/audio), front-end React/TypeScript for agent UIs, familiarity with evaluation tooling (TruLens, PromptFoo), or domain knowledge in [industry focus].