Role Overview

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.
- Robust 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.

📌 Senior Software Engineer – AI Applications (Agentic AI & Graph) (Hyderabad)
🏢 Agivant Technologies
📍 Hyderabad