Role & Responsibilities

Role Summary

Key Responsibilities

- Design and implement end-to-end AI/ML solutions from data ingestion to deployment.
- Architect scalable and secure AI systems using cloud platforms.
- Work on Generative AI use cases including LLMs, prompt engineering, and fine-tuning.
- Collaborate with cross-functional teams to translate business requirements into AI solutions.
- Develop and manage data pipelines and model lifecycle (MLOps).
- Ensure model performance, scalability, reliability, and monitoring in production.
- Stay updated with emerging AI trends and evaluate new tools/technologies.
- Mentor junior engineers and guide best practices in AI development.
- Strong AI Architect Profile with end-to-end ML / Deep Learning / GenAI ownership
- Mandatory (Experience 1) - Must have 6+ years of engineering experience, with atleast 3+ years in AI/ML, or Machine Learning Engineering.
- Mandatory (Experience 2) - Must have atleast 3+ years of hands-on experience building and deploying Generative AI solutions, including LLMs, RAG, AI agents, fine-tuning, prompt engineering, and related technologies.
- Mandatory (Tech skill 1) - Must have worked at architecture level (not engineering-only), designing end-to-end, scalable, secure AI systems through deployment
- Mandatory (Tech skill 1) - Must have strong proficiency in Python along with AI or ML libraries such as TensorFlow, PyTorch and Scikit-learn.
- Mandatory (Tech skill 2) - Must have hands-on experience with Machine Learning, Deep Learning and NLP, including model fine-tuning and LLMs.
- Mandatory (Tech skill 4) - Must have experience with MLOps tooling (MLflow,



Kubeflow or Azure ML), a cloud platform (Azure, AWS or GCP), and containerization (Docker, Kubernetes).
- Mandatory (Mentoring) - Must have led / mentored AI engineers (architect-level leadership)
- Mandatory (Communication) - Must have strong stakeholder management and requirement-gathering experience with US or UK clients.
- Mandatory (Company) - Must come from a B2B IT services or IT consulting background
- Mandatory (Note 1) - CTC is inclusive of 5% variable
- Preferred (Data) - Data engineering concepts, working with large datasets, APIs & microservices
- Preferred (Production) - Experience on production-grade AI systems; open-source AI contributions
- Preferred (Tools) - Exposure to Azure Foundry and Databricks Agent Bricks.
- Preferred (Certifications) - Certifications in AI, ML or cloud platforms.

Perks, Advantages and Work Culture

- Group medical insurance of ₹5 lakhs is included in the benefits package, along with meal allowances

Pay: ₹1,800,000.00 - ₹3,000,000.00 per year

Application Question(s):

- What GenAI frameworks have you worked with and since when?
- If not in Chennai, are you open to relocating to Chennai?
- Are you comfortable appearing for a face-to-face interview in the office? Even if outstation, final round will be face-face (mandatory)
- Are you available to join immediately or within 15 days in office?
- If you are serving NP, when is your last working day?
- What is your notice period in days? (15)
- What is your current CTC in LPA?
- What is your expected CTC in LPA? (30)

Experience :

- overall: 6 years (required)

Work Location: In person

📌 Ai/ml Architect (Genai, Python) (Chennai)
🏢 OptimHire
📍 Chennai