Senior AI Engineer

• Design and scale agentic AI systems to support long-running, complex workflows using orchestration frameworks such as LangGraph, CrewAI, or AutoGen.
• Develop systematic evaluation and benchmarking pipelines using G‑Eval, RAGAS, and LLM‑as‑a‑Judge approaches to measure performance, hallucinations, and latency.
• Implement advanced retrieval-augmented generation (RAG) strategies, including multi-stage re‑ranking, hybrid search, and query expansion for high-precision knowledge retrieval.
• Optimize model inference performance using quantization approaches such as AWQ and GGUF, along with caching strategies for cost‑efficient high throughput.
• Collaborate closely with Data Science and DevOps teams to transition experimental prototypes into hardened, production-ready APIs.
• Implement safety guardrails, red‑teaming workflows, and alignment mechanisms to ensure outputs meet industry regulations and brand‑safety standards.

We offer

• Flexible working hours
• Professional onboarding and training options
• Powerful team looking forward to working with you
• Career coaching and development opportunities
• Health and Insurance benefits.

The essential requirements of the job include:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
• Minimum of 6 years of overall software engineering experience, with at least 3 years focused on LLM application development and deployment.
• Hands-on experience with parameter-efficient fine-tuning techniques such as LoRA and QLoRA.
• Strong proficiency in PyTorch or JAX.
• Expert-level experience with LangChain, LlamaIndex, or Haystack, along with scaling vector databases such as Pinecone, Weaviate, or Milvus.
• Proven experience building custom evaluation datasets and tracking experiments using tools such as Weights & Biases or MLflow.
  • Strong understanding of LLMOps, including CI/CD pipelines, prompt versioning, and model endpoint management.