Senior AI Engineer – Agentic Platform
Amtech Software (company site, opens in a new tab)6+ yrsBengaluruOn-siteDirect career pageEst. 25–40 LPA
Posted on 1 Sept
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at Amtech Software
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Amtech Software you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Own the design and technical direction of the Agentic Platform that enables AI-driven workflows across multiple Amtech software products.
- Develop and maintain headless, MCP-native AI orchestration and data access layers that ensure governed, real-time interactions with enterprise data.
- Deploy, monitor, and optimize AI agents and inference endpoints on AWS, ensuring scalability, cost control, and integration with product teams and engineering functions.
Minimum Requirements
- Bachelor's Degree in Computer Science, Software Engineering, Data Science, or related field.
- 6+ years of software engineering experience, including 2+ years building production systems with large language models.
- Strong Python programming skills and hands-on experience with major LLM APIs (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock).
- Proven experience deploying and operating production workloads on AWS (Lambda, ECS/EKS, S3, IAM, CloudWatch).
Ideal Candidate Profile
- Experienced in setting technical direction and acting as a technical reference for engineering teams without formal management.
- Skilled in building reusable AI agent platforms and integrating agentic AI frameworks like LangChain or LangGraph into enterprise products.
- Comfortable working with production AI systems involving governed customer data, with fluency in ML engineering and MLOps practices for collaboration with data science and operations teams.