Role at a glance
- Job function
-
AI & Data Generative AI Engineering Large Language Model (LLM) Engineering MLOps & ML Infrastructure
- Salary
- Not Disclosed
- Location
- Pune Maharashtra India
- Work arrangement
- Hybrid
- Employment
- Full-time
- Education
- Bachelor's
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About the role
Original posting provided by Citi
The Applications Development Group Manager (SVP) will serve as a senior engineering leader and technical authority responsible for driving the architecture, delivery, and scaling of enterprise-grade software platforms with a core focus on Generative AI and Agentic AI systems. The ideal candidate blends 10+ years of robust full-stack and distributed backend engineering leadership with deep hands-on expertise in frontier AI architectures, multi-agent frameworks, LLMOps, and enterprise AI governance.
1. Core Software Engineering & Architecture Leadership
•Hands-on Engineering Leadership: Extensive track record in designing, architecting, and delivering large-scale, high-throughput enterprise software applications.
•Backend & Enterprise Stack: Deep mastery of Java/J2EE enterprise ecosystem, multithreading, concurrency patterns, memory management, and asynchronous event-driven architectures.
•Modern Web & API Engineering: Proven experience in modern web technologies (HTML5, CSS3, React.js/modern JavaScript frameworks) and RESTful API design, microservices architecture, and API governance.
•Engineering Fundamentals: Strong command of Object-Oriented Design (OOPS/SOLID), Design Patterns, Data Structures, Algorithms, and distributed computing principles.
2. Generative AI, Foundation Models & Context Engineering
•Foundation Models & LLM Fundamentals: Deep theoretical and practical understanding of foundation models, Large Language Models (LLMs), embeddings, tokenization mechanics, attention mechanisms, and context-window optimization.
•Advanced Context Engineering: Hands-on mastery of production context management, including dynamic context layering, prompt chaining, context compression, memory pruning/offloading, and session-state persistence to maximize token efficiency, provenance, and output reliability.
•Advanced Prompt Engineering: Expertise in few-shot prompting, directional stimulus prompting, programmatic prompt pipelines, and automated prompt optimization frameworks.
3. Agentic AI, Multi-Agent Orchestration & Interoperability
•Multi-Agent System Architecture: Proven experience architecting and deploying production-grade agentic workflows using frameworks such as Google Agent Development Kit (ADK), LangGraph or OpenAI Agents SDK.
•Orchestration Patterns: Practical implementation of multi-agent patterns, including hierarchical supervisor/worker topologies, sequential planning, dynamic routing, reflection loops, and peer-to-peer collaboration.
•Agent Harness Engineering & Tooling: Strong grasp of agent harness mechanics, execution boundaries, sandboxing, feedback loops, human-in-the-loop (HITL) integration, and deterministic tool execution.
•Interoperability Protocols: Expertise in emerging agent communication and integration protocols, specifically:
•Model Context Protocol (MCP) for standardized tool, data, and service integration.
•Agent2Agent (A2A) protocols for inter-agent communication and task delegation across distributed systems.
4. Retrieval-Augmented Generation (RAG) & Knowledge Graphs
•Advanced RAG Architectures: Deep hands-on experience designing production RAG pipelines utilizing hybrid search, re-ranking models, parent-document/hierarchical chunking, multi-vector representations, and self-corrective RAG mechanisms.
•Vector Databases & Search Engines: Proficiency with enterprise vector storage solutions
5. LLMOps, Cloud & Infrastructure
•Containerization & Orchestration: Production mastery of Docker containerization and Kubernetes (OpenShift/EKS/GKE) cluster management, auto-scaling, and GPU/accelerator allocation.
•DevOps & LLMOps Pipelines: Deep knowledge of CI/CD automation, model registry workflows, automated regression testing, versioning (Git, DVC), continuous integration pipelines for prompts/models.
•Modern Python Web Frameworks: Strong proficiency in Python with direct development experience in modern asynchronous frameworks (FastAPI, AsyncIO) and high-performance data ingestion pipelines
Recommended Qualifications:
- 13+ years of relevant experience
- Experience in applications development
- Experience in management
- Experience managing global technology teams
- Working knowledge of industry practices and standards
- Consistently demonstrates clear and concise written and verbal communication
Education:
- Bachelor’s degree/University degree or equivalent experience
- Master’s degree preferred
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Job Family Group:
Technology------------------------------------------------------
Job Family:
Applications Development------------------------------------------------------
Time Type:
Full time------------------------------------------------------
Most Relevant Skills
Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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About the company
Citi
Large Enterprise
Citi is a global financial services corporation that offers a wide range of financial products and services, including consumer banking, credit, investment banking, and wealth management. With a presence in nearly 100 countries, Citi serves millions of customers, from individuals and small businesses to large corporations and governments. The company is dedicated to innovation and sustainability, actively working to support economic growth while addressing environmental and social challenges. Citi’s commitment to providing exceptional service and fostering diverse talent makes it a prominent choice for students aspiring to build a career in finance and banking.