About this Role:

Smart Food Secure, a global Quality and Food Safety Management SaaS company, is looking for an AI Engineer with proven experience building and deploying AI capabilities within real software products .

We value demonstrated production AI experience over years of experience . We are looking for a hands-on engineer who can take AI solutions from concept → architecture → prototype → evaluation → production .

Technical Skills

- LLMs & Prompt Engineering: OpenAI/Azure OpenAI, Claude, Gemini; system/few-shot prompting, context engineering and optimization.
- Structured Outputs & Tool Calling: Schema-based outputs and function/tool calling with APIs, databases, and application services.
- Agentic AI: Multi-step workflows, state/tool orchestration and human-in-the-loop controls using LangGraph, LlamaIndex, Semantic Kernel, MCP, or equivalent.
- Advanced RAG: Document parsing, chunking, embeddings, vector databases, hybrid search, reranking, citations, grounding, and hallucination reduction.
- Document & Multimodal AI: OCR, PDFs, images, tables, document extraction, classification, and validation.
- Evals & Observability: LLM-as-a-judge, automated evaluation, regression testing and tracing using Promptfoo, DeepEval, LangSmith, Langfuse, or equivalent.
- Performance & Reliability: Model routing, caching, streaming/SSE, retries, fallback handling, rate-limit management, latency and cost optimization.
- Core Engineering: Expert Python, FastAPI, asyncio, REST APIs, SQL/NoSQL, MongoDB, Git, automated testing, Docker and CI/CD.
- Cloud & Security: Azure/AWS, AI services, scalable deployment, monitoring, prompt-injection protection,



secure RAG, tenant isolation and data privacy.

Proven AI Expeirience - Required Candidates must demonstrate at least two meaningful AI solutions they personally built , preferably deployed in production. You should be able to explain:

- End-to-end architecture and your personal contribution
- Models, frameworks and technologies selected
- How the AI was integrated into the core product
- RAG, agents, document AI or other AI techniques used
- How accuracy, hallucinations and reliability were measured
- Security and data privacy controls
- Production scale, latency and cost
- Technical challenges and how you solved them
- Measurable customer or business outcomes

Candidates should be prepared to demonstrate and technically defend their previous AI work during the interview.

What we are looking for:

A strong AI + software engineer who has shipped AI into real products , understands how to make AI accurate, secure, scalable, observable and cost-effective, and can independently take an AI use case from idea to production.

2–4+ years of relevant AI/ML/software engineering experience preferred. Proven production AI capability matters more than years of experience or academic credentials.

Application Requirement:

Submit your resume plus details of two AI solutions you personally built :

Problem → Architecture → Your contribution → Technology → Evaluation/Accuracy → Production scale → Business outcome

GitHub, demos, architecture diagrams or other evidence of your work are strongly encouraged.

We are looking for AI builders—not simply candidates familiar with AI terminology.

📌 AI Engineer / Applied AI Engineer (Bangalore Metropolitan Area)
🏢 Smart Food Safe : Quality u0026 Food Safety Management Software
📍 Bangalore Metropolitan Area