Job Description
Key Responsibilities
AI & Machine Learning Development
- Design, develop, and deploy AI/ML models for business use cases.
- Build and optimize machine learning pipelines from data preparation to model deployment.
- Develop predictive, classification, recommendation, and NLP solutions.
- Fine-tune and evaluate foundation models and LLMs.
Generative AI Solutions
- Design and implement Generative AI applications using LLMs.
- Develop Retrieval-Augmented Generation (RAG) solutions.
- Create prompt engineering frameworks and reusable AI workflows.
- Integrate AI copilots, chatbots, and virtual assistants into enterprise platforms.
- Implement AI governance, monitoring, and responsible AI practices.
Data Engineering & Integration
- Collaborate with Data Engineers and Data Scientists to prepare training datasets.
- Develop APIs and microservices for AI model consumption.
- Integrate AI services with enterprise systems and cloud platforms.
Model Deployment & Monitoring
- Deploy AI solutions using MLOps best practices.
- Monitor model performance, accuracy, drift, and reliability.
- Ensure scalability, security, and compliance requirements are met.
Required Technical Skills
AI / ML Technologies
- Machine Learning Algorithms
- Deep Learning
- Natural Language Processing (NLP)
- Generative AI
- Large Language Models (LLMs)
- Prompt Engineering
- Vector Databases
Programming Languages
- Python (Mandatory)
- SQL
- Optional: Java, JavaScript, or Scala
AI Frameworks & Libraries
- TensorFlow
- PyTorch
- Scikit-learn
- LangChain
- LlamaIndex
- Hugging Face Transformers
- OpenAI APIs / Azure OpenAI
Vector Databases
- Pinecone
- Weaviate
- ChromaDB
- FAISS
Cloud & MLOps
- Azure AI Services / Azure OpenAI
- AWS Bedrock / SageMaker
- Google Vertex AI
- MLflow
- Docker
- Kubernetes
- CI/CD Pipelines
Database Technologies
- SQL Server
- PostgreSQL
- MongoDB
- Cosmos DB
Leadership & Soft Skills
- Strong analytical and problem-solving skills.
- Excellent communication and stakeholder management.
- Ability to translate business problems into AI-driven solutions.
- Experience working in Agile/Scrum environments.
- Strong collaboration with cross-functional teams.
Preferred Qualifications
- Experience building enterprise AI assistants and chatbots.
- Hands-on experience with RAG architectures and vector search.
- Knowledge of Responsible AI, AI Safety, and AI Governance.
- Exposure to Agentic AI frameworks and autonomous AI workflows.
- Experience with Retail, E-commerce, BFSI, Healthcare, or Supply Chain domains.
Educational Qualification
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
Preferred Certifications
- Microsoft Azure AI Engineer Associate (AI-102)
- Microsoft Azure Data Scientist Associate (DP-100)
- AWS Machine Learning Specialty
- Google Professional Machine Learning Engineer
- TensorFlow Developer Certificate
Key Competencies
- Artificial Intelligence
- Generative AI
- Machine Learning
- Prompt Engineering
- LLM Development
- NLP
- RAG Architecture
- MLOps
- Data Analytics
- Innovation & Problem Solving
Required Technical Skills
AI / ML Technologies
- Machine Learning Algorithms
- Deep Learning
- Natural Language Processing (NLP)
- Generative AI
- Large Language Models (LLMs)
- Prompt Engineering
- Vector Databases
Programming Languages
- Python (Mandatory)
- SQL
- Optional: Java, JavaScript, or Scala
AI Frameworks & Libraries
- TensorFlow
- PyTorch
- Scikit-learn
- LangChain
- LlamaIndex
- Hugging Face Transformers
- OpenAI APIs / Azure OpenAI
Vector Databases
- Pinecone
- Weaviate
- ChromaDB
- FAISS
Cloud & MLOps
- Azure AI Services / Azure OpenAI
- AWS Bedrock / SageMaker
- Google Vertex AI
- MLflow
- Docker
- Kubernetes
- CI/CD Pipelines
Database Technologies
- SQL Server
- PostgreSQL
- MongoDB
- Cosmos DB
Leadership & Soft Skills
- Strong analytical and problem-solving skills.
- Excellent communication and stakeholder management.
- Ability to translate business problems into AI-driven solutions.
- Experience working in Agile/Scrum environments.
- Strong collaboration with cross-functional teams.
Preferred Qualifications
- Experience building enterprise AI assistants and chatbots.
- Hands-on experience with RAG architectures and vector search.
- Knowledge of Responsible AI, AI Safety, and AI Governance.
- Exposure to Agentic AI frameworks and autonomous AI workflows.
- Experience with Retail, E-commerce, BFSI, Healthcare, or Supply Chain domains.
Educational Qualification
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
Preferred Certifications
- Microsoft Azure AI Engineer Associate (AI-102)
- Microsoft Azure Data Scientist Associate (DP-100)
- AWS Machine Learning Specialty
- Google Professional Machine Learning Engineer
- TensorFlow Developer Certificate
Key Competencies
- Artificial Intelligence
- Generative AI
- Machine Learning
- Prompt Engineering
- LLM Development
- NLP
- RAG Architecture
- MLOps
- Data Analytics
- Innovation & Problem Solving
At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.
Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.
We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.
