AI Engineer

Role: AI Engineer

Location: Gurugram, Haryana, India

Workplace type: Hybrid i.e. 6 days a week (2-3 days per week in-office, rest remote)

About the Role

We are looking for an AI Engineer who can build production-grade AI systems—not just connect applications to third-party APIs.

You will work across the AI development lifecycle: selecting and fine-tuning models, designing multi-agent architectures, building evaluation pipelines, deploying inference systems, and improving model performance using real-world feedback. This role is ideal for an engineer who enjoys experimentation but also knows how to turn prototypes into reliable, scalable products.

Experience working in LegalTech, compliance, finance, healthcare, or another domain involving sensitive and complex data is highly preferred.

Responsibilities

• Design, build, and deploy LLM-powered applications and intelligent workflows.
• Fine-tune and adapt open-source models using techniques such as LoRA, QLoRA, SFT, and preference optimization.
• Build multi-agent systems with effective planning, tool usage, memory, routing, and human-in-the-loop controls.
• Develop RAG pipelines, including document processing, embeddings, retrieval, reranking, and citation generation.
• Create evaluation frameworks for accuracy, hallucination, latency, cost, safety, and task completion.
• Optimize inference performance and deploy models in cloud or self-hosted environments.
• Work with product, engineering, and domain experts to translate complex legal or business workflows into AI systems.
• Monitor production performance and continuously improve models using user feedback and evaluation data.

Requirements

• 2+ years of experience in AI, machine learning, NLP, or applied LLM engineering.
• Strong Python and software engineering fundamentals.
• Hands-on experience with PyTorch, Hugging Face Transformers, or similar frameworks.
• Experience fine-tuning, evaluating, and deploying language models.
• Understanding of transformer architectures, embeddings, tokenization, context management, and inference optimization.
• Experience building agentic or multi-agent systems using frameworks such as LangGraph, AutoGen, CrewAI, or custom orchestration.
• Familiarity with vector databases, structured outputs, tool calling, and retrieval systems.
• Ability to independently take an AI feature from experimentation to production.

Preferred Qualifications

• Experience at a LegalTech startup or working with legal documents, contracts, case law, compliance, or document review.
• Experience with model serving tools such as vLLM, TGI, Triton, or Ollama.
• Familiarity with LLM observability, guardrails, prompt-injection risks, and data privacy.
• Experience working in a fast-moving startup environment.

What We Value

We value engineers who understand models deeply, question default approaches, run disciplined experiments, and build AI systems that are accurate, explainable, secure, and useful in production.