AI Engineer (Across Seniority)

About the Role

mylynk.ai is an AI headhunting firm hiring AI engineering talent for several client companies. These companies are seeking AI engineers capable of building and deploying production AI systems. Applying through mylynk.ai provides access to multiple opportunities with one application.

Key Responsibilities

• Design, build, and operate LLM-powered systems in production, including RAG pipelines, agentic workflows, tool calling, structured extraction, and conversational AI.
• Develop voice agents and real-time speech systems, covering turn-taking, streaming, telephony, and multilingual support.
• Implement model evaluation, building harnesses, benchmark suites, and observability for quality, latency, and cost.
• Perform fine-tuning and RLHF / preference optimization on domain-specific data.
• Handle MLOps: deploy and scale ML/LLM services using FastAPI, Docker, Kubernetes, AWS, and CI/CD.
• Work across various model providers (OpenAI, Anthropic, Gemini, open-source) to select the appropriate model for each task.

Requirements & Tech Stack

• Strong software engineering fundamentals with a focus on Python.
• Experience with FastAPI and async is a plus.
• Hands-on experience with LLM APIs, RAG, embeddings/vector databases, and agent frameworks (e.g., LangGraph, Pydantic AI).
• An evidence-driven mindset with a focus on measurement.
• Ownership mentality, thriving in fast-moving, resource-lean startup environments.
• Experience with model evaluation, including building harnesses, benchmark suites, and observability.
• Experience with MLOps for deploying and scaling ML/LLM services.

Qualifications

• Interns and freshers with strong proof-of-work (e.g., GitHub, side projects, hackathons).
• Senior and lead engineers with 5-8+ years of experience, including infra/MLOps/team leadership.

Nice to Have

• Speech-to-text, OCR, multilingual NLP (Indian languages are a plus).
• Fine-tuning, RLHF/DPO/PPO, and experiment tracking tools (e.g., W&B, MLflow).
• Experience with model serving at scale (e.g., vLLM, Triton, Ray Serve).
• Domain exposure in: legal tech, BFSI/fintech, agritech/govtech, developer tools.

Locations

• Mostly Bengaluru (on-site/hybrid).
• Select roles in Hyderabad and San Francisco.