Job Responsibilities :

Design, build, deploy, and maintain scalable Agentic AI systems for complex business workflows and autonomous task execution.

Develop AI agents capable of reasoning, planning, memory management, tool usage, and multi-step decision-making.

Build generative AI applications using LLMs, prompt engineering, function calling, structured outputs, RAG pipelines, and AI APIs.

Design and implement single-agent and multi-agent architectures for workflow automation, research, analysis, and operational efficiency.

Develop and integrate AI agents with enterprise applications, databases, APIs, SaaS platforms, and internal tools.

Build and optimize knowledge retrieval systems using vector databases, embeddings, semantic search, and memory frameworks.

Collaborate with product, engineering, and business teams to identify high-impact AI use cases and translate them into scalable technical solutions.

Optimize agent performance for accuracy, reliability, latency, cost efficiency, and user experience.

Build orchestration frameworks, evaluation pipelines, guardrails, and testing systems to ensure robust agent behavior.

Implement monitoring, observability, logging, and continuous improvement processes for production AI systems.

Ensure responsible AI practices, including security, privacy, governance, bias mitigation, and compliance requirements.

Mentor junior engineers, conduct technical reviews, and contribute to AI engineering standards and best practices.

Stay updated with advancements in Agentic AI, LLMs, reasoning models, multi-agent systems, MCP, RAG architectures, and emerging AI technologies.





Required

Proven 5+ years of experience in AI, Machine Learning, Data Science, or related engineering roles.

Strong programming skills in Python and experience with SQL.

Hands-on experience with LLMs, RAG, vector databases, prompt engineering, GenAI tools and AI APIs.

Experience with agent frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.

Solid understanding of AI system design, orchestration, evaluation, and deployment.

Experience with cloud platforms, APIs, Docker, and MLOps practices.

Experience deploying AI solutions on AWS, GCP, Azure, or similar cloud platforms.

Strong understanding of APIs, microservices, and scalable backend integrations.

Excellent analytical, communication, and problem-solving skills.

Ability to work in agile, cross-functional environments.

Desired

Experience with consumer-facing digital products.

Experience building production-grade Agentic AI or multi-agent systems.

Contributions to open-source AI projects, research, or technical communities.

Knowledge of MCP, A2A, knowledge graphs, and advanced retrieval architectures.

Knowledge of MLOps, CI/CD, Docker, Kubernetes, and model monitoring.

Experience with recommendation systems or personalization engines.

Prior mentoring or team leadership experience.

Minimum Educational Qualification:

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field or Diploma in Computer Science / IT with relevant hands-on experience or Equivalent practical experience or certifications in software development

📌 Architect - Deloitte (Mumbai)
🏢 TRIGENT SOFTWARE PRIVATE
📍 Mumbai