Agentic AI Developer

Open Insights, LLC; India; Remote; INR 1,200,000 - 1,800,000; Full time

Job summary

A leading tech firm in India is seeking an experienced Agentic AI Developer to architect and implement cutting-edge autonomous systems combining data-driven intelligence with scalable workflows. Candidates should have a strong background in Generative AI, AI/ML, and systems design. This role requires collaboration with cross-functional teams, focusing on delivering impactful solutions across various industries.

Qualifications

• 3 – 5+ years of applied experience in AI/ML, Generative AI, and agentic systems.
• Expertise with cloud platforms and containerization.
• Strong ability to design human-in-the-loop AI workflows.

Responsibilities

• Design and implement advanced agentic AI architectures.
• Develop autonomous agents leveraging LLMs and tool integrations.
• Orchestrate workflows combining Generative AI and human-AI collaboration.

Skills

Data science

Machine learning

AI solution design

LLMs

Generative AI applications

Data manipulation

Problem-solving

Stakeholder engagement

Education

Bachelor’s or Master’s degree in Computer Science or related fields

Tools

AWS

Azure

Docker

Kubernetes

Pandas

NumPy

Scikit-learn

PyTorch

TensorFlow

Job description

Open Insights is seeking talented Agentic AI Developers with expertise at the intersection of Generative AI, Data Science, and agent-driven systems. This role focuses on architecting and implementing autonomous AI agents that combine data-driven intelligence with orchestrated, safe, and scalable workflows, delivering business-aligned impact across industries.

Responsibilities

• Design and implement advanced agentic AI architectures, including single- and multi-agent systems, with capabilities for tool orchestration, memory management, and retrieval-augmented generation (RAG).
• Develop and productionize autonomous agents that leverage LLMs, multi-agent frameworks (e.g., LangChain, AutoGPT, Semantic Kernel, CrewAI), memory modules, and tool integrations.
• Orchestrate workflows that combine Generative AI, predictive modeling, and decision-making under human-AI collaboration paradigms.
• Build robust data pipelines for ingestion, transformation, feature engineering, training, evaluation, and observability.
• Translate business requirements into scalable system architectures, aligning technical design with measurable client outcomes and ROI.
• Integrate safety, guardrails, and governance controls into agentic systems to ensure reliability, ethical compliance, and regulatory adherence.
• Collaborate cross-functionally on experimental design to enable agent planning, self-reflection, and iterative self-improvement loops.
• Stay ahead of industry trends, contributing thought leadership on applied multi-agent systems and emerging capabilities in Generative AI.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or quantitative disciplines.
• 3 – 5+ years of applied experience in AI/ML, Generative AI, and agentic systems.
• Expertise with cloud platforms (AWS, Azure, GCP), containerization (Docker, Kubernetes), and MLOps/LLMOps practices.
• Working knowledge of data systems (SQL/NoSQL, vector databases, data lakes) and retrieval-augmented generation (RAG).
• Strong problem-solving, systems thinking, and ability to design enterprise-ready, human-in-the-loop AI workflows.

Skills and Abilities

• Strong background in data science, machine learning, and AI solution design
• Proven hands-on expertise with LLMs, agentic workflows, and Generative AI applications.
• Practical experience with data manipulation (Pandas, NumPy), ML libraries (Scikit-learn, PyTorch, TensorFlow), and production deployment best practices.
• Familiarity with AI orchestration frameworks, multi-agent coordination, and integration with APIs/tools.
• Demonstrated experience in deploying at least one production-ready Agentic AI solution that can be showcased, highlighting scalability, reliability, and business impact.
• Proficiency in end-to-end delivery methodologies (Agile, hybrid), with demonstrable ownership of projects from ideation to deployment.
• Strong stakeholder engagement, documentation, and communication skills for translating insights into action.
• Ability to balance technical depth with business context and adapt to evolving enterprise challenges.