AI / AI Engineering Lead

Coditude; Pune District; On-site; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

n/a

Job summary

Coditude in Pune, India seeks an experienced AI Engineering Lead with 5+ years overall and 2–3+ years in AI/LLM. You will bridge client needs and high-quality production AI solutions, architecting and delivering robust data pipelines and production models.

You will mentor engineers, ensure solution quality, and engage directly with clients to translate business requirements into secure AI software, while evaluating emerging frameworks and integrating multi-agent architectures.

Qualifications

• 5+ years of total software engineering experience, with 2–3+ years building, fine-tuning, and deploying production AI/LLM solutions.
• Proven experience in model fine-tuning, dataset prep, and evaluating local open-weights vs API models.
• Experience with multi-agent systems, MCP integrations, and low-code/orchestration tools.
• Solid background in ETL, data preprocessing, vector databases and data flows for RAG/AI engines.
• CI/CD for AI workflows, automated evaluation, regression testing, and ModelOps telemetry.
• Strong consultant-facing communication and leadership skills.

Responsibilities

• Lead hands-on development, fine-tuning and evaluation of models to client specs.
• Design multi-agent architectures using MCP and orchestration platforms.
• Build and optimize ETL pipelines and data ingestion for AI datasets.
• Implement CI/CD automation, automated evaluation, QA guardrails, and monitoring.
• Collaborate with clients to translate business requirements into AI architectures.
• Adapt and integrate emerging AI frameworks and infrastructure as needed.
• Provide technical guidance and mentorship to engineers, conducting code reviews.
• Ensure data security, privacy, and compliance in all deliverables.

Skills

AI Engineering

Model Fine-Tuning

MLOps

Data Pipelines

CI/CD for AI

Multi-Agent Systems

Langfuse

LLM

Python

PyTorch

LangChain

Leadership

Tools

n8n

LangGraph

AutoGen

LlamaIndex

Langfuse

Job description

We are looking for an experienced AI / AI Engineering Lead (5+ years overall experience, with 2–3+ years dedicated to AI/LLM engineering) to join our technical leadership team. In this role, you will bridge client needs and high-quality technical implementation—architecting and delivering production-level AI solutions, fine-tuned models, agentic workflows, and robust data pipelines.

You will act as both a hands-on technical architect and a consultative technical lead who mentors engineers, ensures high solution quality, and engages directly with clients to turn complex business requirements into cutting-edge, secure AI software.

Key Responsibilities

• Model Training, Fine-Tuning & Architecture: Lead hands-on development, fine-tuning (e.g., LoRA, QLoRA, domain adaptation), and evaluation of open-weights and proprietary models tailored to client specifications and production requirements.
• Agentic Workflows & MCP Implementation: Design and orchestrate complex multi-agent architectures , leveraging protocols such as Model Context Protocol (MCP) , agentic frameworks, and workflow automation platforms (e.g., n8n, LangGraph, AutoGen).
• Data Engineering & ETL Pipelines: Build, optimize, and maintain high-throughput ETL and data ingestion pipelines for unstructured/structured data processing, vector indexing, and model training/inference datasets.
• AI CI/CD & Automated Evaluation: Implement CI/CD automation pipelines for AI systems , integrating continuous evaluation, automated QA guardrails, benchmarking, and ModelOps telemetry (e.g., Langfuse, TruLens).
• Client Engagement & Solutioning: Collaborate directly with clients to understand business requirements, define technical scope, and design optimal, business-aligned AI architectures.
• Framework Adaptability: Quickly evaluate, adapt, and integrate emerging AI frameworks, vector databases, and AI infrastructure based on project needs.
• Leadership & Mentorship: Provide technical guidance and mentorship to junior and mid-level engineers, conduct rigorous code reviews, and drive engineering best practices across teams.
• Quality & AI Security: Ensure end-to-end technical quality, performance, safety, and reliability of all client deliverables, enforcing strict data security, privacy, and compliance protocols.

Required Qualifications & Skills

• Overall & AI Experience: 5+ years of total software engineering experience, with 2–3+ years of dedicated hands-on experience building, fine-tuning, and deploying production AI/LLM solutions.
• Model Training & Fine-Tuning (Must-Have): Proven, practical experience in model fine-tuning , dataset preparation, hyperparameter tuning, and evaluating local open-weights vs. API-based models.
• Agentic Systems & MCP: Demonstrated experience building multi-agent systems , agentic tool-use pipelines, Model Context Protocol (MCP) integrations, and low-code/orchestration platforms like n8n or custom agent frameworks.
• Data & ETL Infrastructure: Solid background in designing ETL pipelines , data preprocessing, vector database ingestion, and managing data flows for RAG and AI engines.
• AI CI/CD & MLOps/ModelOps: Experience setting up CI/CD pipelines for AI workflows , automated LLM evaluation suites, regression testing, and production observability/monitoring tools (e.g., Langfuse).
• Adaptable AI Tech Stack: Deep practical knowledge across modern AI toolchains (Python, PyTorch/Hugging Face, LangChain/LlamaIndex, FastAPI, vector databases, Docker, Ollama/local inference platforms).
• Consultative Communication & Leadership: Strong client-facing communication skills with a track record of translating business problems into technical AI specs and mentoring engineering pods to delivery.