The Role
Design, develop, deploy, and monitor AI and machine learning solutions, including predictive models, NLP applications, generative AI, LLMs, RAG systems, copilots, and chatbots. Build ML pipelines, APIs, microservices, and enterprise integrations using cloud and MLOps practices. Responsibilities include model evaluation, performance monitoring, responsible AI governance, scalability, security, and collaboration with data, engineering, and business stakeholders.
Summary Generated by Built In
Key ResponsibilitiesAI & Machine Learning Development
Responsibilities- 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.
- 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.
- 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.
- Deploy AI solutions using MLOps best practices.
- Monitor model performance, accuracy, drift, and reliability.
- Ensure scalability, security, and compliance requirements are met.
Required Technical SkillsAI / ML Technologies
Qualifications- Machine Learning Algorithms
- Deep Learning
- Natural Language Processing (NLP)
- Generative AI
- Large Language Models (LLMs)
- Prompt Engineering
- Vector Databases
- Python (Mandatory)
- SQL
- Optional: Java, JavaScript, or Scala
- TensorFlow
- PyTorch
- Scikit-learn
- LangChain
- LlamaIndex
- Hugging Face Transformers
- OpenAI APIs / Azure OpenAI
- Pinecone
- Weaviate
- ChromaDB
- FAISS
- Azure AI Services / Azure OpenAI
- AWS Bedrock / SageMaker
- Google Vertex AI
- MLflow
- Docker
- Kubernetes
- CI/CD Pipelines
- SQL Server
- PostgreSQL
- MongoDB
- Cosmos DB
- 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.
- 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.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 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
- Artificial Intelligence
- Generative AI
- Machine Learning
- Prompt Engineering
- LLM Development
- NLP
- RAG Architecture
- MLOps
- Data Analytics
- Innovation & Problem Solving
Required Technical SkillsAI / ML Technologies
About UsAt 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.- Machine Learning Algorithms
- Deep Learning
- Natural Language Processing (NLP)
- Generative AI
- Large Language Models (LLMs)
- Prompt Engineering
- Vector Databases
- Python (Mandatory)
- SQL
- Optional: Java, JavaScript, or Scala
- TensorFlow
- PyTorch
- Scikit-learn
- LangChain
- LlamaIndex
- Hugging Face Transformers
- OpenAI APIs / Azure OpenAI
- Pinecone
- Weaviate
- ChromaDB
- FAISS
- Azure AI Services / Azure OpenAI
- AWS Bedrock / SageMaker
- Google Vertex AI
- MLflow
- Docker
- Kubernetes
- CI/CD Pipelines
- SQL Server
- PostgreSQL
- MongoDB
- Cosmos DB
- 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.
- 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.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 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
- Artificial Intelligence
- Generative AI
- Machine Learning
- Prompt Engineering
- LLM Development
- NLP
- RAG Architecture
- MLOps
- Data Analytics
- Innovation & Problem Solving
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.
Skills Required
- Machine learning algorithms, deep learning, NLP, generative AI, LLMs, prompt engineering, and vector databases
- Python programming
- SQL
- Experience with TensorFlow, PyTorch, Scikit-learn, LangChain, LlamaIndex, Hugging Face Transformers, and OpenAI or Azure OpenAI APIs
- Experience with vector databases such as Pinecone, Weaviate, ChromaDB, or FAISS
- Experience with cloud and MLOps technologies including Azure AI Services, AWS Bedrock or SageMaker, Google Vertex AI, MLflow, Docker, Kubernetes, and CI/CD pipelines
- Experience with SQL Server, PostgreSQL, MongoDB, or Cosmos DB
- Strong analytical, problem-solving, communication, stakeholder management, and cross-functional collaboration skills
- Experience working in Agile or Scrum environments
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field
- 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 in Retail, E-commerce, BFSI, Healthcare, or Supply Chain domains
- Microsoft Azure AI Engineer Associate certification
- Microsoft Azure Data Scientist Associate certification
- AWS Machine Learning Specialty certification
- Google Professional Machine Learning Engineer certification
- TensorFlow Developer Certificate
Zensar Technologies Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zensar Technologies and has not been reviewed or approved by Zensar Technologies.
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Retirement Support — A 401(k) with company match and immediate vesting is highlighted, with broad fund options available.
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Wellbeing & Lifestyle Benefits — Work-life balance, remote/hybrid flexibility, and supportive teams are emphasized as strengths that enhance the overall experience.
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Parental & Family Support — Inclusive policies such as parental leave and access to EAP and dependent medical coverage are promoted across regions.
Zensar Technologies Insights
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The Company
What We Do
Zensar is a leading experience, engineering, and technology solutions company. We conceptualize, build, and manage digital products for Forbes Global 2000 clients across the hi-tech engineering, banking and financial services, insurance, manufacturing and consumer services verticals. With proven excellence across five core areas, including experience services, advanced engineering services, data engineering and analytics, foundation services, and application services, our solutions leverage industry-leading platforms to help our clients be competitive, agile, and disruptive while moving with velocity through change and opportunity. Zensar’s expansive ecosystem of 60+ technology partners, including Oracle, Salesforce, SAP, Guidewire, Automation Anywhere, Adobe, and UiPath, enables us to deliver comprehensive solutions to clients, facilitating seamless integration and allowing them to leverage cutting-edge technologies and tools for enhanced business outcomes. Zensar is part of the USD 4.4 billion RPG Group. With headquarters in Pune, India, our 10,500+ employees, representing over 50 nationalities, work from 30+ locations across North America, UK/Europe, and South Africa. Visit us at www.zensar.com
