Senior Software Engineer – AI Applications (Agentic AI & Graph)

Agivant Technologies; Hyderabad; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Agivant Technologies is seeking a proactive AI Engineer to lead the design and development of production-ready agentic AI systems, focused on fraud investigation use cases and modular reusable libraries for multi-customer deployment.

You will own end-to-end delivery from concept to scalable production code, working in a small team with strong ownership and minimal guidance. Expect collaboration with customers and cross-functional teams to translate requirements into working software.

Qualifications

• Expertise in agentic AI, LLM orchestration, tool integration, and multi-step workflows.
• Proficiency with graph databases, graph algorithms, knowledge graphs, RAG, and GraphRAG architectures.
• Experience in full-stack application development and interactive data visualization.

Responsibilities

• Design and build agentic AI and graph-based applications, including autonomous agents and tool-calling workflows.
• Develop intuitive interfaces, investigation visualizations, workflows, authentication, and permissions systems.
• Implement state management, agent memory, orchestration, observability, auditing, evaluation and monitoring frameworks.

Skills

Agentic AI

LLM orchestration

Graph databases

Full-stack development

Cloud platforms

Security & RBAC

Observability

Tools

Kubernetes

CI/CD

Infrastructure as code

Job description

We are seeking a proactive, product-minded AI Engineer to lead the design and development of production-ready, agentic AI systems. In this role, your primary focus will be building an agentic AI application for fraud investigation, with the broader objective of creating a reusable library of applications that can be configured and deployed for various customers and prospects.

We need self-starters who thrive in small teams, possess strong ownership, and can take complex customer problems from initial concept to scalable production code with minimal guidance.

Key Responsibilities

• System & Workflow Design: Design and build complete agentic AI and graph-based applications, including autonomous agents, tool-calling workflows, GraphRAG, vector search, MCP tools, APIs, and human-in-the-loop processes.
• Interface & Security Integration: Develop intuitive customer-facing interfaces, investigation visualizations, workflows, authentication, and permission systems.
• Agent Operations: Implement robust state management, agent memory, orchestration, observability, auditing, evaluation, and monitoring frameworks.
• Architecture & Scalability: Build secure, reliable, and reusable architectures capable of multi-tenant deployment across public cloud, private cloud, hybrid, and on-premises environments.
• Productization: Abstract reusable capabilities from customer-specific configurations to build a modular, scalable application library.
• Engineering Standards: Maintain high code quality through automated test coverage, CI/CD pipelines, infrastructure-as-code, and production-readiness practices.
• Customer & Team Collaboration: Work directly with customers and cross-functional teams to translate requirements into working software, rapidly iterating on feedback.

Technical Profile

• Expertise in Agentic AI, LLM orchestration, tool integration, and multi-step workflows.
• Proficiency with graph databases, graph algorithms, knowledge graphs, RAG, and GraphRAG architectures.
• Experience in full-stack application development and interactive data visualization.
• Hands-on experience with APIs, MCP tools, event-driven services, and system integrations.
• Strong understanding of enterprise security, including authentication, authorization, and RBAC.
• Solid grasp of agent memory systems, observability, and evaluation metrics.
• Proficiency with cloud platforms (AWS, GCP, or Azure), Kubernetes, and containerization.
• Experience deploying applications across hybrid and on-premises environments.
• Practice with CI/CD automation, automated testing, and production operations.

Ideal Candidate Characteristics

• Strong system design, analytical problem-solving, and full-stack engineering skills.
• High degree of ownership, urgency, and comfort operating autonomously through ambiguity.
• Ability to balance rapid delivery with long‑term scalability, security, and maintainability.
• Product-oriented mindset, capable of turning custom client requests into reusable solutions.
• Commitment to engineering best practices, code quality, and automated testing.
• Strong communication skills to articulate technical decisions, trade‑offs, and risks clearly to non‑technical stakeholders.

What Success Looks Like

• Rapidly translating customer use cases into reliable, working software.
• Owning core product features end-to-end—from architectural design to cloud deployment.
• Converting bespoke customer implementations into standard, configurable enterprise products.
• Balancing short‑term client delivery with the build‑out of a long‑term application library.