Sr. AI Engineer

Photon; Dallas (TX); Sur place; USD 120 000 - 180 000; Plein temps

Résumé du poste

Photon is seeking an AI Engineer to design, build, and optimize prompts and AI-driven solutions for enterprise contexts. You will implement MCP-enabled workflows, secure data handling, and knowledge-grounded architectures across regulated environments.

The role emphasizes hands-on development with LLMs, RAG, and tool-calling patterns, collaborating with product and engineering to deliver reliable AI platforms.

Qualifications

• Hands-on experience with prompt engineering for LLMs.
• Experience designing prompts, system prompts, few-shot prompts and tuning.
• Develop AI-powered apps using LLM APIs and RAG workflows.
• Knowledge of HIPAA-aligned data privacy and secure handling.

Responsabilités

• Design, develop, and optimize prompts for LLMs to improve accuracy and outcomes.
• Build Agentic AI solutions using planning, reasoning, memory, and multi-step execution.
• Develop MCP tools to securely interact with enterprise data sources.
• Design architectures, tool-calling frameworks, and context management strategies.
• Collaborate with product, architects, and engineering to translate requirements into AI solutions.
• Implement retrieval-augmented generation and knowledge grounding patterns.
• Define evaluation and testing for agent performance and reliability.
• Ensure AI solutions meet security, governance, and responsible AI standards.
• Support deployment, monitoring, troubleshooting, and continuous improvement of AI agents.
• Contribute to design documentation and engineering best practices for AI platforms.

Connaissances

Prompt engineering

LLM APIs

RAG workflows

Knowledge retrieval

NLP fundamentals

HIPAA security

Outils

MCP servers

Vector databases

Semantic search

Description du poste

AI Engineer with strong hands‑on experience in prompt engineering, LLM response optimization, and AI application development. The ideal candidate can design prompts, improve model output quality, help LLMs understand user input, and build reliable, context‑aware AI solutions.

Key Responsibilities

• Design, develop, and optimize prompts for Large Language Models (LLMs) to improve accuracy, reliability, and business outcomes.
• Build and configure Agentic AI solutions that leverage planning, reasoning, memory, and multi‑step task execution capabilities.
• Develop and integrate MCP (Model Context Protocol) tools, enabling AI agents to securely discover and interact with enterprise systems, APIs, and data sources.
• Design agent architectures, tool‑calling frameworks, retrieval mechanisms, and context management strategies.
• Collaborate with product managers, architects, and engineering teams to translate business requirements into AI‑driven solutions.
• Implement Retrieval‑Augmented Generation (RAG), knowledge grounding, and context orchestration patterns.
• Define evaluation frameworks and prompt testing methodologies to measure agent performance, quality, and reliability.
• Ensure AI solutions adhere to security, compliance, governance, and responsible AI standards.
• Support deployment, monitoring, troubleshooting, and continuous improvement of AI agents and MCP‑enabled workflows.
• Contribute to architecture reviews, technical design documentation, and engineering best practices for AI platforms.

Required Skills

• Hands‑on experience with LLMs such as GPT, Claude, Gemini, Llama, or similar models.
• Strong prompt engineering skills, including prompt templates, system prompts, few‑shot prompting, and response tuning.
• Develop AI‑powered applications using LLM APIs, RAG workflows, enterprise data sources, and backend services.
• Knowledge of RAG, embeddings, vector databases, semantic search, and knowledge retrieval workflows.
• Ability to evaluate and improve AI responses for accuracy, relevance, completeness, tone, and instruction following.
• Understanding of NLP concepts, hallucination mitigation, prompt injection risks, guardrails, and responsible AI practices.
• Knowledge of healthcare data privacy and secure sensitive‑data handling, including HIPAA‑aligned PHI/PII practices, data minimization, de‑identification, masking, access controls, auditability, and responsible use of healthcare data in AI workflows.
• Experience with MCP servers, cloud platforms, APIs, backend services, and production deployment is preferred.
• Experience integrating AI agents with healthcare, health records, or regulated industry systems.