Senior Generative AI Engineer with Java Full-stack - Vice President
Citi · Pune · 12+ yrs experience · Posted 2026-07-18
Tech stack: Django, Docker, FastAPI, Flask, Java, Kubernetes, MongoDB, Python
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About the role
We are seeking a highly experienced and innovative Senior Generative AI Engineer with over 12 years of industry experience, including a strong background in Java Full-stack development, to join our dynamic team. The ideal candidate will be instrumental in designing, developing, and deploying cutting-edge generative AI solutions that drive significant business impact. This role requires deep hands-on expertise in building scalable enterprise-grade AI systems, coupled with a solid understanding of software development best practices and robust architecture patterns, with a proven track record in both Java and Python ecosystems.
Responsibilities: - Lead the engineering and execution of scalable enterprise Generative AI solutions from concept to production.
- Design, develop, and implement advanced AI models and systems, with a focus on generative AI, leveraging large language models (LLMs) and agentic AI architectures.
- Integrate AI services into existing enterprise systems by designing and implementing robust, high-performance APIs.
- Apply expert-level proficiency in Python frameworks (e.g., FastAPI, Django, Flask, PySpark) for AI development and system integration.
- Leverage significant past experience in Java development for building robust, scalable enterprise applications and integrating AI components within existing Java-based systems.
- Utilize deep understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems, to inform solution design.
- Gain hands-on experience with relevant AI frameworks and orchestration tools such as Google ADK, LangGraph, LangChain, AutoGen, and CrewAI.
- Leverage extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., Scikit-Learn, NumPy, Pandas) to build and optimize AI models.
- Develop, deploy, and integrate Model Context Protocols (MCPs) into sophisticated agentic AI systems.
- Demonstrate deep familiarity and practical application of large language models (LLMs) such as ChatGPT, Claude, Gemini, and Llama within agentic systems.
- Champion software development best practices, including version control (Git), CI/CD pipelines, comprehensive testing, and rigorous code reviews.
- Ensure application resiliency and adhere to strong security principles in all AI projects.
- Apply expertise in system design, application development, and operational stability for critical AI initiatives.
- Utilize deep experience with application and data architecture patterns and designs, emphasizing API-First Design, microservices, and event-driven architectures.
- Leverage managed services and existing platforms effectively to accelerate development and deployment.
- Possess hands-on experience with containerization and orchestration technologies, specifically Docker and Kubernetes.
- Proactively identify and solve complex technical challenges with excellent analytical, innovative, pragmatic, and creative problem-solving skills.
Qualifications: - 12+ years of progressive experience in software engineering, with a significant focus on Generative AI.
- Prior hands-on experience in Java Full-stack development is required.
- Expert-level proficiency in Python, including experience with frameworks such as FastAPI, Django, Flask, or PySpark.
- Solid understanding of core AI concepts: knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems.
- Demonstrated hands-on experience with generative AI frameworks/orchestration tools like Google ADK, LanGraph, LangChain, AutoGen, or CrewAI.
- Extensive experience with machine learning frameworks (TensorFlow, PyTorch) and libraries (Scikit-Learn, NumPy, Pandas).
- Proven experience in creating, deploying, and integrating MCPs into agentic AI systems.
- Deep familiarity with large language models (LLMs) (e.g., ChatGPT, Claude, Gemini, Llama) and their application in agentic systems.
- Strong experience in designing and implementing robust APIs for AI services.
- Proficient in software development best practices: Git, CI/CD, comprehensive testing, and code reviews.
- Strong understanding of agile methodologies, application resiliency, and security principles in AI.
- Proven expertise in system design, application development, and ensuring operational stability.
- Deep experience with application and data architecture patterns and designs, including API-First Design, microservices, and event-driven architectures.
- Hands-on experience with Docker and Kubernetes.
- Proficiency in database technologies such as Oracle, Postgres, or MongoDB.
- Excellent analytical, innovative, and problem-solving skills.
- Previous experience within the banking or financial services industry, understanding regulatory environments and specific challenges, is a plus.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related technical field.
- Bachelor’s University degree
- Master’s degree preferred
Qualifications
- 12+ years of progressive experience in software engineering, with a significant focus on Generative AI.
- Prior hands-on experience in Java Full-stack development is required.
- Expert-level proficiency in Python, including experience with frameworks such as FastAPI, Django, Flask, or PySpark.
- Solid understanding of core AI concepts: knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems.
- Demonstrated hands-on experience with generative AI frameworks/orchestration tools like Google ADK, LanGraph, LangChain, AutoGen, or CrewAI.
- Extensive experience with machine learning frameworks (TensorFlow, PyTorch) and libraries (Scikit-Learn, NumPy, Pandas).
- Proven experience in creating, deploying, and integrating MCPs into agentic AI systems.
- Deep familiarity with large language models (LLMs) (e.g., ChatGPT, Claude, Gemini, Llama) and their application in agentic systems.
- Strong experience in designing and implementing robust APIs for AI services.
- Proficient in software development best practices: Git, CI/CD, comprehensive testing, and code reviews.
- Strong understanding of agile methodologies, application resiliency, and security principles in AI.
- Proven expertise in system design, application development, and ensuring operational stability.
- Deep experience with application and data architecture patterns and designs, including API-First Design, microservices, and event-driven architectures.
- Hands-on experience with Docker and Kubernetes.
- Proficiency in database technologies such as Oracle, Postgres, or MongoDB.
- Excellent analytical, innovative, and problem-solving skills.
- Previous experience within the banking or financial services industry, understanding regulatory environments and specific challenges, is a plus.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related technical field.
- Bachelor’s University degree
- Master’s degree preferred
Responsibilities
- Lead the engineering and execution of scalable enterprise Generative AI solutions from concept to production.
- Design, develop, and implement advanced AI models and systems, with a focus on generative AI, leveraging large language models (LLMs) and agentic AI architectures.
- Integrate AI services into existing enterprise systems by designing and implementing robust, high-performance APIs.
- Apply expert-level proficiency in Python frameworks (e.g., FastAPI, Django, Flask, PySpark) for AI development and system integration.
- Leverage significant past experience in Java development for building robust, scalable enterprise applications and integrating AI components within existing Java-based systems.
- Utilize deep understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems, to inform solution design.
- Gain hands-on experience with relevant AI frameworks and orchestration tools such as Google ADK, LangGraph, LangChain, AutoGen, and CrewAI.
- Leverage extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., Scikit-Learn, NumPy, Pandas) to build and optimize AI models.
- Develop, deploy, and integrate Model Context Protocols (MCPs) into sophisticated agentic AI systems.
- Demonstrate deep familiarity and practical application of large language models (LLMs) such as ChatGPT, Claude, Gemini, and Llama within agentic systems.
- Champion software development best practices, including version control (Git), CI/CD pipelines, comprehensive testing, and rigorous code reviews.
- Ensure application resiliency and adhere to strong security principles in all AI projects.
- Apply expertise in system design, application development, and operational stability for critical AI initiatives.
- Utilize deep experience with application and data architecture patterns and designs, emphasizing API-First Design, microservices, and event-driven architectures.
- Leverage managed services and existing platforms effectively to accelerate development and deployment.
- Possess hands-on experience with containerization and orchestration technologies, specifically Docker and Kubernetes.
- Proactively identify and solve complex technical challenges with excellent analytical, innovative, pragmatic, and creative problem-solving skills.