Engineering Manager-AI/ML

Important Note (Please Read Before Applying)

🚫 Do NOT apply if:

• You have less than 10 years or more than 12 years of experience

You do not have hands-on Engineering Manager-AI/ML 6+ experience

• You are on a notice period longer than 30 days
• You are looking for Hybrid only (role is Hybrid in Bangalore)
• You are a fresher or unrelated background (e.g., support, testing only, non-Java roles)

✅ Apply ONLY if you meet ALL criteria above. Random / irrelevant applications will not be processed.

About Company : They balance innovation with an open, friendly culture and the backing of a long-established parent company, known for its ethical reputation. We guide customers from what’s now to what’s next by unlocking the value of their data and applications to solve their digital challenges, achieving outcomes that benefit both business and society.

Job Title: Engineering Manager-AI/ML

Location: Hyderabad

Experience: 8+ Years (STRICTLY)

Employment Type: Permanent

Notice Period: Immediate Joiners -30 Days Only

About the Company

Our client is a trusted global innovator of IT and business services, present in 50+ countries. They specialize in digital & IT modernization, consulting, managed services, and industry-specific solutions. With a commitment to long-term success, they empower clients and society to move confidently into the digital future.

Job Overview:

About the Role

Job Title : Engineering Manager-AI/ML

Internal Role level : Level 5

Overall Industry Experience : 8 to 12 years

Job Description :

We are seeking a highly motivated and experienced ML Manager/Lead Data Scientist to join our

growing ML/GenAI team.

You will play a key role in designing, developing and productionalizing ML/GenAI applications by

evaluating models, training and/or fine tuning them. As a lead, you require a deep

understanding of both machine learning algorithms and software architecture. You need to take

ownership of projects from conception to deployment, collaborating with engineers and

stakeholders to ensure successful project delivery.

What we're looking for:

● At least 5 years of experience in designing & building ML/AI applications for customer

and deploying them into production

● At least 8 years of Software engineering experience in building Secure, scalable and

performant applications for customers.

● At least 2 years of experience leading and mentoring ML/data science teams( 4+ team

members)

● Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen

AI.

● Design, develop, and operationalize existing ML models by fine tuning, personalizing it.

● Evaluate machine learning models and perform necessary tuning.

● Develop prompts that instruct LLM to generate relevant and accurate responses.

● Collaborate with data scientists and engineers to analyze and preprocess datasets for

prompt development, including data cleaning, transformation, and augmentation.

● Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to

improve LLM performance.

● Lead the end-to-end design and architecture of scalable, reliable, and cost-effective

Generative AI solutions. This includes designing RAG (Retrieval-Augmented Generation)

pipelines, agentic workflows, and model fine-tuning strategies.

● Hands on customer experience with RAG solution or fine tuning of LLM model.

● Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud

platform involving data warehouses, machine learning platforms, dashboards or CRM

tools.

● Experience working with the end-to-end steps involving but not limited to data cleaning,

exploratory data analysis, dealing outliers, handling imbalances, analyzing data

distributions (univariate, bivariate, multivariate), transforming numerical and categorical

data into features, feature selection, model selection, model training and deployment.

● Act as the senior-most developer, writing clean, high-quality, and scalable code. This

includes building core components for prompt engineering, vector search, data

processing, model evaluation, and inference serving.

● Proven experience building and deploying machine learning models in production

environments for real life applications

● Good understanding of natural language processing, computer vision or other deep

learning techniques.