Artificial Intelligence Engineering – Manager/Lead

Crisil; Maharashtra; On-site; INR 1,500,000 - 2,500,000; Full time

Benefits offered by this job

Continuous learning budget

Remote flexibility

Opportunities for certifications and workshops

Job summary

A financial analytics firm is looking for an AI Engineering Manager based in India to lead the development of end-to-end AI solutions. The role entails managing a team of engineers, designing AI platforms, and implementing advanced frameworks. Candidates should have 9 to 12 years of relevant experience, expertise in machine learning and data science tools, and a degree in computer science or mathematics. The position offers a hybrid work model with opportunities for continuous learning and industry-leading research involvement.

Qualifications

• 9 to 12 years of experience in machine learning and AI development.
• Experience in large language models and deploying data science solutions.
• Hands-on experience with cloud platforms and data sourcing.

Responsibilities

• Lead a team of AI engineers to develop GenAI solutions.
• Design scalable AI/ML platforms and manage their lifecycle.
• Integrate advanced AI frameworks for analytics workflows.

Skills

Machine learning

Large language models

Python

Data science libraries

Cloud platforms (Azure, AWS, GCP)

SQL and NoSQL databases

Excellent communication skills

Education

Bachelor’s or Master's degree in Computer Science

Bachelor’s or Master's degree in Mathematics

Tools

TensorFlow

PyTorch

HuggingFace

LangChain

Haystack

Job description

Artificial Intelligence Engineering – Manager: Lead the path for execution of E2E Artificial Intelligence Solutions.

Experience: 9-12 Years (Minimum 7 Years in AI Development)

Industry: Credit Rating & Financial Analytics

As an AI Manager, you’ll spearhead the design, development, and deployment of GenAI solutions that power our next-gen analytics platforms. Your leadership will empower a high-performing team and deliver interpretable, production-ready LLM-powered solutions that redefine industry standards in data‑driven decision‑making.

What will your day look like?

• Lead and mentor a dynamic team of 3–5 AI engineers, fostering a collaborative, growth‑first culture.
• Design and architect scalable AI/ML platforms and infrastructure that support enterprise-wide AI initiatives, including multi‑agent systems, RAG pipelines, and model lifecycle management.
• Implement agentic AI design patterns, building on frameworks like Autogen, LangGraph, CrewAI – or develop bespoke agentic architectures from the ground up.
• Integrate advanced GenAI frameworks, leveraging recent advancements such as Model Context Protocols (MCP) and Agent‑to‑Agent (A2A) frameworks for complex analytic workflows.
• Mentor and guide technical teams, elevating architectural rigor, code quality, and operational excellence while staying current with emerging AI technologies and industry best practices.
• Oversee the complete lifecycle of AI solutions: data acquisition and curation, feature engineering, model training (SFT, RLHF), evaluation and guardrails, CI/CD, deployment, monitoring, and iterative improvement.
• Implement observability and reliability for AI systems (offline/online evals, data/model drift). Promote transparency through open‑source contributions; GitHub or Kaggle visibility is highly valued.

What's in your toolkit?

• A bachelor's or master's degree in computer science, statistics, mathematics, engineering, or a related field.
• 9 to 12 years of experience in machine learning, computer vision with a special emphasis on large language models.
• Proficiency in Python and its data science libraries such as pandas, numpy, TensorFlow, PyTorch and HuggingFace, LangChain or Haystack.
• Define patterns for Agentic AI (planning, tool‑use/function calling, memory, feedback loops, multi‑agent collaboration), and standardize frameworks for orchestration and evaluation at scale.
• Should be hands on with latest in RAG practices and SLM fine tuning.
• Hands‑on experience deploying and maintaining data science solutions on cloud platforms like Azure, AWS, or GCP.
• Has experience in sourcing data from SQL and NoSQL db. A basic knowledge of databases is a must.
• A Kaggle profile that reflects your expertise will be an added advantage.
• Excellent communication and presentation skills are mandatory.
• The ability to balance independent and collaborative work in a fast‑paced environment.

Educational Background:

• Bachelor’s or Master’s degree from premier Indian institutes (IITs, IISc, NITs, BITS, IIITs etc.) in:
• Computer Science, or
• Mathematics or related quantitative fields.
• Hybrid work model combining remote flexibility and collaborative office culture in Pune or Mumbai.
• Continuous learning budget for certifications, workshops, and conferences.
• Opportunities to work on industry‑leading AI research and shaping the future of financial services.