AI Engineer III – Agentic Platform

About Vista Equity Partners:

Vista Equity Partners is a leading global investment firm focused exclusively on enterprise software, data, and technology-enabled businesses. With over $100B in assets under management and a portfolio of 90+ software product companies worldwide, Vista accelerates growth through operational excellence, shared expertise, and long-term partnership. In India, Vista's presence continues to expand with 45+ portfolio companies employing more than 17,000 professionals.

Through its Agentic AI Factory, Vista is embedding Generative AI across its global portfolio, enabling companies to integrate intelligent, responsible AI into products, operations, and decision-making.

About Amtech:

Amtech LLC is a leading provider of enterprise software solutions for the packaging and manufacturing industries, helping businesses streamline operations, improve productivity, and drive sustainable growth.

Role Description:

Amtech LLC is seeking a Senior AI Engineer to build and scale the Agentic Platform behind Amtech AI Intelligence, a headless, MCP-native intelligence layer across packaging and labels, and data that is callable by any AI, on any screen. This role takes Amtech's first production agent pattern and turns it into a reusable platform component that extends cleanly to EnCore, LabelTraxx, Siteline, Scorekeeper, and future use cases. This is a senior, largely self-directed role: you'll set technical direction for the platform, make build-vs-buy calls on agent tooling, and be a technical reference point for the Forward Deployed Engineers embedding it into product pods.

Job Description:

Headless, MCP-Native Architecture

• Build business logic that runs independent of any screen.
• Expose Amtech capabilities as MCP-described tools so any AI model can call them.

Orchestration and Agent Execution

• Build and maintain the LLM orchestration layer that turns model output into safe, governed, tool-using actions.
• Implement and extend agent workflows using frameworks such as LangChain/LangGraph and the Model Context Protocol (MCP).

Retrieval and Model Integration

• Build and tune RAG pipelines for grounding agent responses in Amtech's own data.
• Integrate model-agnostic LLM providers via a common provider abstraction, avoiding vendor lock-in.

Governed On-Prem Data Access (the Data Agent)

• Build and maintain the Data Agent, which reads EnCore and other customer data directly for inferencing.
• Ensure every agent action passes governed approval gates before it executes, with a complete, queryable audit trail.

Building Amtech AI Intelligence Capabilities

• Extend the platform into delivered capabilities such as Schedule Intelligence, Order and Customer Intelligence, Docs and Knowledge, and Forecast and KPI Intelligence.

Plugging Into Amtech's Broader Agent Portfolio

• Reuse patterns from Amtech's 10+ active agents rather than rebuilding them.
• Support extending agent-building to Sales, Support, and Customer Success on the same governed orchestration, RAG, and audit foundation.

Scaling the Platform Pattern Across Product Lines

• Turn Amtech's first production agent pattern into a reusable platform component that other product pods can adopt without a rebuild.
• Partner with Forward Deployed Engineers to validate the platform against real workflows and feed learnings back into the roadmap.

Deployment, Monitoring, and Cost Control

• Deploy agents and inference endpoints on AWS (e.g., Lambda, ECS/EKS, SageMaker) and integrate them into existing APIs and microservices.
• Set up evals, cost controls, and basic observability to catch regressions, drift, or runaway spend.

Bridging into ML Engineering and MLOps

• Bring classical ML engineering and MLOps fluency (feature stores, model registries, CI/CD for models, drift monitoring) to partner with Data Science, ML Engineering, and MLOps functions.
• As a senior technical voice, weigh in on production practices across agentic and classical ML workloads.

Required Qualifications:

• Bachelor's Degree in Computer Science, Software Engineering, Data Science, or related field.
• 4-6 years of software engineering experience, including 2+ years hands-on building production systems with large language models.
• Demonstrated experience setting technical direction and reviewing the work of other engineers.
• Strong Python programming skills.
• Practical experience with prompt engineering, tool/function calling, and agent frameworks (e.g., LangChain, LangGraph).
• Experience integrating at least one major LLM provider API (OpenAI, Anthropic, Azure OpenAI, or AWS Bedrock).
• Hands-on AWS experience (e.g., Lambda, ECS/EKS, S3, IAM, CloudWatch) deploying and operating production workloads.
• Experience with model inferencing, including optimizing latency, throughput, and cost for LLM or ML workloads.
• Experience building or consuming RAG pipelines and working with vector databases.
• Working knowledge of classical ML engineering and MLOps practices.
• Familiarity with Docker and containerized deployment.
• Working knowledge of Git and CI/CD practices.

Preferred Qualifications:

• Experience with the Model Context Protocol (MCP) or similar agent-tool integration standards.
• Experience building governed, read-only data access layers (audit logging, guardrails, least-privilege access).
• Exposure to Kubernetes and cloud AI/inferencing platforms (AWS Bedrock, AWS SageMaker).
• Experience working with ERP, MES, or other industrial/manufacturing data environments.
• Prior experience embedding directly with a product team or customer-facing engineering effort.
• Familiarity with performance monitoring tools (e.g., Prometheus, Grafana, Datadog).

Why Join Amtech:

At Amtech, you will drive meaningful financial impact in a growing enterprise software organization while benefiting from Vista's world-class ecosystem. You'll collaborate with talented peers, leverage cross-portfolio learning programs, and help shape the future of Amtech's financial operations and systems.