The AI Integration Engineer builds the connective tissue between LLM APIs, existing product systems, and end users. They are not training models. They are integrating, orchestrating, and deploying AI capabilities into production software, reliably, securely, and at scale.

Key Responsibilities:

● Integrate LLM APIs (Anthropic Claude, OpenAI GPT-4o, AWS Bedrock, Google

Gemini) into backend services and user-facing products

● Design and implement RAG pipelines: document ingestion, chunking strategy,

vector store selection, retrieval tuning

● Build agentic workflows using frameworks such as AgentCore, LangChain,

LlamaIndex, or custom orchestration patterns

● Manage prompt engineering, prompt versioning, and prompt evaluation

frameworks

● Implement guardrails for LLM outputs: validation, content filtering, fallback logic

● Monitor AI system performance: latency, cost-per-query, accuracy drift, token

usage

● Collaborate with frontend engineers to surface AI capabilities in product UIs

● Own the AI integration layer in the SDLC, from spec to CI/CD to production

observability

Education and Experience:

A degree (Masters preferred) in Computer Science, Engineering, Artificial Intelligence, Data Science, Applied Mathematics, or related fields.
Minimum 5+ years of hands-on experience in engineering.

Technical Skills:

3+ years backend or fullstack experience; strong API design and consumption skills
Proven experience integrating LLM APIs (any major provider) into production applications, not just prototypes
Proficiency in Python and/or TypeScript/Node.js
Hands-on experience with RAG vector databases Pinecone, Weaviate, pgvector etc), embedding models, chunking strategies.
Understanding of prompt engineering: system prompts, few-shot examples, chain-of-thought, structured output
Solid grasp of API security, rate limiting, cost management for LLM-based services
Experience with AWS or another major cloud platform
Desirable Skills:

Experience with agentic frameworks: AgentCore, LangChain, LlamaIndex,
CrewAI, AutoGen, or similar
Familiarity with multi-modal AI (vision, audio) or function calling / tool use
Understanding of fine-tuning workflows even if not hands-on
Experience using AI coding assistants to accelerate their own development workflow

Soft Skills:

Highly motivated, self-driven, entrepreneurial mindset, and capable of solving complex analytical problems under high-pressure situations.
Ability to work with cross-functional and cross-regional teams.
Ability to lead a team of Data/AI professionals and work with senior management, technological experts, and the product team.
Excellent written and verbal communication skills, comfortable with client communication.
Good leadership skills - ability to motivate and mentor team members, ability to plan and make sound decisions, ability to negotiate tactfully with the client and team.
Results-oriented, customer-focused with a passion for resolving tough technical and operational challenges.
Possess excellent analytical and problem-solving abilities.
Good documentation skills.
Experienced with Agile methodologies like Scrum/Kanban