Senior Software Engineer - Agentic AI

Reposted 17 Days Ago
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Chennai, Tamil Nadu
In-Office
Senior level
Cloud • Software
The Role
Lead development of agentic AI systems, mentor engineers, and drive projects utilizing LLMs and orchestration frameworks. Manage AI model lifecycle and collaborate with stakeholders.
Summary Generated by Built In

Job Description:

About the Role

Kaleris is looking for a Senior Software Engineer with deep expertise in agentic AI systems, LLM orchestration, and production-scale deployment. You will shape and deliver strategic GenAI features, mentor team members, and drive applied AI projects utilizing frameworks like LangGraph.

Responsibilities

  • Architect and lead development of advanced agentic AI systems using LangGraph or similar frameworks.
  • Own the full model lifecycle: research, solution design, prototyping, optimization, testing, and production deployment.
  • Lead and mentor the AI team, setting best practices for model quality, scalability, and responsible AI.
  • Integrate LLMs with enterprise data, orchestration systems, and workflow automation (RAG, vector search, API development).
  • Collaborate with engineering, product, and business stakeholders to define AI-driven product features and roadmaps.
  • Conduct technical reviews, establish coding standards, and ensure codebase robustness.
  • Optimize AI infrastructure for performance, cost, and reliability (cloud, MLOps, container orchestration).
  • Champion innovation: stay ahead of industry trends, bring actionable insights and drive adoption of new AI technologies.
  • Ensure AI model governance, fairness, and compliance with ethical/organizational standards.

Requirements

  • Bachelor’s or Master’s (PhD a plus) in Computer Science, Engineering, or related field.
  • 5+ years building and deploying AI/ML systems (at least 2+ years with LLMs or agentic frameworks in production). Proven track record building agentic patterns (ReAct, Agentic Loops), multi-agent systems, and graph-based orchestration engines.
  • Proven experience with Python, LLM technologies, advanced prompt engineering, and agent workflows (LangGraph, LangChain, CrewAI), async programming (asyncio), and backend frameworks (FastAPI, Django).
  • Deep understanding of cloud AI platforms (AWS/Azure), containerization (Docker/Kubernetes), and CI/CD for ML ops.
  • Demonstrated leadership in AI solution design, code and architecture reviews, and mentoring junior engineers.
  • Experience with retrieval pipelines, vector databases, and cloud-native architectures.
  • Proficient with full-stack AI development: APIs, microservices, data pipelines.
  • Strong knowledge of MLOps tools, monitoring, versioning, and responsible AI.
  • Excellent communication, influencing, and cross-team collaboration skills.
  • Intellectual curiosity, a drive for innovation, and a passion for making an impact with AI.

Highly Desired

  • Experience building enterprise agentic AI or autonomous workflow orchestration systems.
  • Expertise with neural search, advanced RAG, and enterprise data integration.
  • Certifications in AI/ML, cloud, or relevant technologies.
  • Logistics/supply chain software experience is a strong plus.

Why Join Kaleris?

  • Competitive salary & comprehensive benefits
  • Inclusive, diverse, and collaborative team culture
  • The chance to build AI products at the frontier of agentic intelligence for supply chain

Kaleris is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Top Skills

AWS
Azure
Ci/Cd
Crewai
Django
Docker
Fastapi
Kubernetes
Langchain
Langgraph
Llm Technologies
Python
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The Company
Alpharetta, Georgia
245 Employees

What We Do

Kaleris is a leading provider of cloud-based supply chain execution and visibility technology solutions. Many of the world's largest brands rely on Kaleris to provide mission-critical technology for yard management, transportation management, maintenance and repair operations, terminal operating systems, and ocean carrier and vessel solutions. By consolidating supply chain execution software assets across major nodes and modes, we address the dark spots and data gaps that cause friction and inefficiency in the global supply chain.

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