Overview:

Prodapt is the largest specialized player in the Connectedness industry. As an AI-first strategic technology partner, Prodapt provides consulting, business reengineering, and managed services for the largest telecom and tech enterprises building networks and digital experiences of tomorrow. A ServiceNow-invested company, Prodapt has been recognized by Gartner as a Large, Telecom-Native, Regional IT Service Provider. A “Great Place To Work® Certified” company, Prodapt employs over 5,000 technology and domain experts across the Americas, Europe, India, Africa, & Japan. Prodapt is part of the 130-year-old business conglomerate The Jhaver Group, which employs over 32,000 people across 80+ locations globally.

We are seeking a highly skilled Senior AI/ML Developer to join our Agentic AI Platform Team. In this role, you will design, develop, and deploy production-grade AI agents and intelligent automation solutions powered by Large Language Models (LLMs). You will work closely with platform architects and engineering teams to build scalable multi-agent systems that directly support field technicians and enterprise operations.

The ideal candidate combines deep expertise in Generative AI, Agentic AI frameworks, Retrieval-Augmented Generation (RAG), and cloud-native software engineering with strong Python development skills and a passion for building enterprise-scale AI solutions.

Responsibilities:

• Agentic AI & Multi-Agent Systems

  • Design and develop autonomous, goal-oriented AI agents using frameworks such as LangGraph, LangChain, MCP, and internal frameworks (PyVegas, VEGAS, DPF).
  • Build and enhance multi-agent orchestration pipelines with advanced state management, conditional routing, task delegation, and fault-tolerant error recovery mechanisms.
  • Implement tool-calling agents that support parallel execution, sequential enrichment workflows, and intelligent summarization.
  • Design and develop multimodal AI capabilities, including vision-enabled image analysis and document processing.

  Generative AI & LLM Engineering

  • Develop, fine-tune, and optimize Large Language Models (LLMs) and Small Language Models (SLMs) for domain-specific business use cases.
  • Design advanced prompt engineering frameworks, dynamic prompt management solutions, and token optimization strategies to improve performance, scalability, and cost efficiency.
  • Integrate with Azure OpenAI and other foundation model platforms utilizing resilient patterns such as circuit breakers, retries, fallback chains, and observability controls.
  • Build real-time conversational AI experiences using streaming technologies such as WebSockets and Server-Sent Events (SSE).

  Retrieval-Augmented Generation (RAG) & Knowledge Systems

  • Design and optimize vector embedding pipelines, intelligent document chunking strategies, semantic search, and hybrid retrieval architectures.
  • Develop advanced RAG solutions leveraging vector databases, hybrid search (semantic and keyword-based retrieval), re-ranking techniques, and Reciprocal Rank Fusion (RRF).
  • Implement Knowledge Graph-based solutions to improve contextual understanding, reasoning, and AI-driven decision-making.

  Software Engineering & Platform Development

  • Develop scalable, secure, and production-ready Python applications using modern AI/ML frameworks and engineering best practices.
  • Build APIs, microservices, and distributed systems that support enterprise AI workloads.
  • Implement robust logging, monitoring, observability, error handling, testing, and performance optimization strategies.
  • Design and maintain CI/CD pipelines for AI model deployment, versioning, and lifecycle management across development, staging, and production environments.
  • Support production deployments by troubleshooting issues, monitoring model performance, and ensuring operational stability.

  Collaboration & Leadership

  • Partner with business stakeholders, architects, and engineering leaders to translate business requirements into scalable AI solutions.
  • Provide technical guidance on model selection, AI architecture, data dependencies, and implementation approaches.
  • Participate actively in Agile ceremonies including sprint planning, backlog refinement, stand-ups, retrospectives, and solution demos.
  • Contribute to architecture reviews, technical design discussions, code reviews, and engineering best practices.

Requirements:

• Must-Have Qualifications

  • Education: Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline.
  • Core Experience: 12+ years of software development experience with strong expertise in Python and enterprise application development.
  • AI Specialization: 2+ years of hands-on experience building Generative AI, Agentic AI, or LLM-based applications in production environments.
  • Required telecom domain experience with strong knowledge of telecommunications systems, OSS/BSS platforms, network operations, customer experience platforms, and telecom data ecosystems, including experience applying AI/ML solutions in telecom environments.

   

  Agentic AI & Generative AI Expertise

  • Extensive experience with Agentic AI frameworks such as LangGraph, LangChain, MCP, or equivalent enterprise agent orchestration platforms.
  • Strong understanding of autonomous agents, multi-agent systems, tool calling, workflow orchestration, memory management, and reasoning frameworks.
  • Expertise in Generative AI technologies including: LLMs, SLMs, Prompt Engineering, Fine-Tuning, Function Calling, Structured Outputs, and Model Evaluation.

  RAG & Knowledge Systems

  • Proven experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.
  • Strong expertise in vector embeddings, vector databases, semantic search, hybrid retrieval architectures, re-ranking / ranking optimization, and document intelligence.
  • Experience with Knowledge Graphs and graph-based reasoning frameworks.

  Software Development & Cloud Technologies

  • Advanced Python programming skills with experience in FastAPI, AsyncIO, HTTPX, SQLAlchemy, and Alembic.
  • Hands-on experience with OpenAI APIs, tool-calling frameworks, streaming APIs, and real-time AI applications.
  • Solid background in PostgreSQL, relational databases, distributed systems, and microservices architecture.
  • Experience with AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, and Scikit-learn.
  • Hands-on experience with AWS (e.g., Bedrock, SageMaker, Lambda, ECS/EKS, S3).

  DevOps & Deployment

  • Experience with multi cloud platforms — familiarity with AWS, Azure and GCP.
  • Strong understanding of CI/CD pipelines, Docker, Kubernetes, model deployment / version control, automated testing / validation, and observability / monitoring solutions.

  Leadership & Collaboration

  • Strong system design and architecture skills.
  • Ability to mentor developers and influence technical direction.
  • Experience collaborating with cross-functional teams, architects, and business stakeholders.
  • Strong communication, problem-solving, and Agile delivery experience.

  Preferred Qualifications

  • Experience in telecommunications and large-scale enterprise platforms.
  • Experience building production multi-agent platforms and AI copilots.
  • Knowledge of model evaluation frameworks, guardrails, AI governance, and responsible AI practices.
  • Experience with Azure AI Foundry, Azure OpenAI, and enterprise-scale AI deployments.