- Company Name
- SWITS DIGITAL Private Limited
- Job Title
- Senior AI Engineer
- Job Description
-
Job Title: Senior AI Engineer
Role Summary: Lead architect and engineer for large‑language‑model and agentic AI solutions, driving end‑to‑end development, deployment, and governance across enterprise platforms while mentoring a high‑performance AI team.
Expectations:
- Deliver production‑ready, scalable AI applications with measurable impact.
- Maintain rigorous safety, compliance, and observability standards.
- Influence and execute enterprise AI strategy and best practices.
Key Responsibilities:
- Evaluate, benchmark, and recommend AI platforms, LLMs, and agent frameworks for business use.
- Design and prototype agentic models capable of multi‑step reasoning and planning.
- Build and fine‑tune LLM applications with retrieval‑augmented generation (RAG) pipelines and vector‑search backends.
- Embed AI capabilities into core enterprise systems (OMS, CRM, loyalty, digital portals).
- Define and enforce AI model deployment, observability, safety, and compliance standards.
- Collaborate with Product, Digital Engineering, and Data Science to create AI‑enabled features and workflows.
- Implement guardrails, privacy controls, and compliance measures for AI services.
- Lead, coach, and grow a team of AI engineers while actively contributing to technical delivery.
Required Skills:
- Deep expertise in LLM fine‑tuning, RAG, embeddings, and vector‑search (Pinecone, Weaviate, Redis Vector, Azure Cognitive Search).
- Strong command of AI/ML frameworks: LangChain, LlamaIndex, Semantic Kernel, Hugging Face.
- Proficiency in cloud‑native AI services (Azure AI/ML & OpenAI, AWS Bedrock, GCP Vertex AI).
- MLOps proficiency (MLflow, Azure Machine Learning, equivalent lifecycle tools).
- Observability tools: Langfuse, Weights & Biases, Application Insights.
- Security & compliance knowledge (OAuth 2.0, RBAC, GDPR, PCI, responsible AI).
- Programming: Python (primary), TypeScript/Node.js for integrations.
- Experience with multimodal AI (vision, speech, structured data) and regulated industry domains (aviation, logistics, finance).
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Engineering, or related field (Master’s or PhD preferred).
- 8+ years of professional experience in software engineering, AI/ML, or data platform development.
- Certifications in AI/ML or cloud platforms (Azure AI, AWS AI, GCP ML) are a plus.