Posted:6 days ago|
Platform:
On-site
Contractual
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.
Our client is a global digital solutions and technology consulting company headquartered in Mumbai, India. The company generates annual revenue of over $4.29 billion (₹35,517 crore), reflecting a 4.4% year-over-year growth in USD terms. It has a workforce of around 86,000 professionals operating in more than 40 countries and serves a global client base of over 700 organizations.
Our client operates across several major industry sectors, including Banking, Financial Services & Insurance (BFSI), Technology, Media & Telecommunications (TMT), Healthcare & Life Sciences, and Manufacturing & Consumer. In the past year, the company achieved a net profit of $553.4 million (₹4,584.6 crore), marking a 1.4% increase from the previous year. It also recorded a strong order inflow of $5.6 billion, up 15.7% year-over-year, highlighting growing demand across its service lines.
Key focus areas include Digital Transformation, Enterprise AI, Data & Analytics, and Product Engineering—reflecting its strategic commitment to driving innovation and value for clients across industries.
Key Responsibilities:
Design, develop, and deploy scalable backend services using Python and FastAPI.
Build and optimize Gen AI pipelines using LangChain, RAG, and prompt engineering techniques.
Knowledge of ML.
Develop and manage agentic AI systems capable of autonomous task execution.
Integrate and fine-tune LLMs using AWS SageMaker, and manage model lifecycle.
Implement secure and efficient data pipelines using S3, Lambda, ECS, and Boto3.
Collaborate with data scientists, ML engineers, and product teams to deliver AI-powered features.
Monitor and optimize system performance, ensuring high availability and low latency.
Stay updated with the latest trends in Gen AI, LLMs, and cloud-native architectures.
LangChain, RAG, Prompt Engineering
LLM orchestration and tool use
Agentic AI frameworks or custom agent design
Strong understanding of LLM APIs (Anthropic etc.)
2–3+ years of experience with AWS services:
SageMaker (model training, deployment, inference)
Lambda, ECS, S3, Boto3
Familiarity with Amazon Bedrock is a strong plus.
Soft Skills:
Strong problem-solving and debugging skills.
Excellent communication and collaboration abilities.
Ability to work in a fast-paced, agile environment.
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