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The job description asks for AI engineering, agentic AI concepts and terminology, building solutions where agents reason, work toward goals, invoke tools or APIs, and take actions, LLMs and modern generative AI architectures, data science fundamentals, React, TypeScript and Next.js. Make sure your resume shows the ones you have, in the words the job uses: applicant tracking systems look for them.

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This is based in Pune District, Maharashtra.

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Sr. Full Stack Engineer with AI

Aptino, Inc.

Pune District, Maharashtra, India

Position: Sr. Full Stack Engineer with AI

Location: Viman Nagar, Pune, MH - Hybrid

Start Date: ASAP (30-60 day notice period is max...ideally sooner)

Shift Time: 4:30 pm to 1:30 am IST

Note: Must have at least 8 years of total experience - Need an engineer who can handle both frontend and backend development

Job Description:

We are looking for a Full-Stack Developer to build production-ready, goal-driven AI agents that reduce the administrative and digital workload placed on technicians, along with the technician-facing interface people use to work with them.

This is not a traditional data science or LLM experimentation role. The ideal candidate is a hands-on AI engineer who has built agents that reason toward a goal, interact with applications and APIs, take actions, and run reliably in production.

Strong full-stack skills matter equally. You will build both the AI and agent capabilities and the front-end experience that lets technicians review, approve, and act on what the agents do.

What You'll Be Doing

AI agents

Design, build, and enhance goal-driven AI agents that take real-world digital actions.
Turn an initial proof of concept into a production-ready agentic solution.
Build workflows where agents complete multi-step tasks independently, with human approval when required.
Work with Anthropic's enterprise Claude platform to develop and enhance AI capabilities.

Front end

Build intuitive, technician-facing interfaces, not just back-end AI functionality.
Turn design specifications and Figma prototypes into responsive, accessible UI components.
Show agent activity, status, and approval requests clearly, so technicians stay in control.

Back end and integration

Develop integrations between AI agents and enterprise systems through APIs.
Use Python and Java for AI, automation, integration, and application development.
Partner with colleagues focused on AI engineering, Snowflake and data engineering, and ServiceNow.

Architecture and quality

Help decide the right architecture and technical approach as the project evolves, rather than implementing predefined features.
Build for production readiness, scalability, reliability, security, and maintainability.

Required Qualifications

AI engineering

Strong hands-on AI engineering experience, with agents that have moved beyond experimentation or basic LLM usage into production.
Strong understanding of agentic AI concepts and terminology.
Experience building solutions where agents reason, work toward goals, invoke tools or APIs, and take actions.
Understanding of LLMs and modern generative AI architectures, plus solid data science fundamentals.

Front end (required)

Hands-on experience building user-facing applications with React and TypeScript, including Next.js or a similar framework.
Strong HTML5, CSS3, and modern JavaScript (ES6+), including responsive layouts with Flexbox and Grid.
Experience with a utility or component styling approach such as Tailwind CSS.
Ability to turn Figma designs into pixel-accurate, accessible, cross-browser interfaces.
Experience consuming REST APIs and managing client-side state, loading states, and error handling.

Back end and integration

Strong full-stack software development experience across back-end and user-facing development.
Strong Python and Java knowledge, and an understanding of how Python applies to AI-driven solutions.
Experience designing, developing, and consuming APIs.

Working style

Comfortable in an evolving environment where requirements and technical approaches change as the team learns.
Strong communication skills, able to discuss technical decisions, trade-offs, and the future of AI with both technical and business stakeholders.

Nice to Have

Experience with Anthropic's Claude platform, Model Context Protocol (MCP), RAG, or workflow tools such as n8n.
Familiarity with Snowflake or other data platforms, and with ServiceNow integrations.
Experience with Node.js, GraphQL, or Django alongside Python and Java.
Cloud and delivery experience: AWS, Docker, CI/CD, and automated testing such as Cypress or Jest.
Experience designing human-in-the-loop approval flows for AI-driven actions.

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