Senior MLOps / AI Platform Engineer

Infopact, Inc.; Arlington (VA); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Equal Opportunity Employer

Job summary

Infopact, Inc. is seeking a senior AI/ML Ops engineer to build and operate AWS-hosted chatbot and orchestration services. The role involves integrating Databricks, vector stores, and enterprise documents with scalable pipelines in a secure AWS environment.

You will work with Python, Docker, Kubernetes, and modern AI tooling to deliver reliable, governed AI solutions and robust observability in production.

Qualifications

• 9+ years of experience in MLOps/cloud/platform/DevSecOps or prod AI development.
• Hands-on AWS stack experience including Bedrock and/or SageMaker, API Gateway, ECS/EKS, ECR, S3, IAM, Secrets Manager, KMS, CloudWatch.
• Containerizing Python apps with Docker and deploying to ECS/EKS/Kubernetes.
• Integrating Databricks REST APIs and Genie OAuth Unity Catalog data.
• Building API-based chatbot/orchestration services with Python (FastAPI/Flask).
• Routing across structured data, RAG, and hybrid QA workflows.
• Connecting AI apps to vector stores (OpenSearch, Bedrock Knowledge Bases, pgvector, Databricks Vector Search).
• Document ingestion pipelines for SharePoint, S3, and other repositories.
• Secure token handling, IAM least privilege, secrets management, and auditability.

Responsibilities

• Build, integrate, deploy, and operate AWS-hosted chatbot and orchestration services.
• Connect to Databricks, vector stores, enterprise documents, and participating websites.
• Develop API-based AI services using Python (FastAPI/Flask).
• Implement CI/CD pipelines and production observability for reliability.

Skills

MLOps

Cloud engineering

Platform engineering

DevSecOps

Production AI

Python

Docker

Kubernetes

API development

FastAPI/Flask

Tools

Databricks REST APIs

Genie Conversation API

SQL Statement Execution API

OAuth authentication

Unity Catalog

ECS

EKS

SageMaker

Bedrock

OpenSearch

Job description

Job Description:

Build, integrate, deploy, and operate the AWS-hosted chatbot and orchestration services, including its connections to Databricks, enterprise documents, vector stores, and participating websites.

• 9+ years of experience in MLOps, cloud engineering, platform engineering, DevSecOps, or production AI application development.
• Hands-on experience building and deploying AI/ML applications using the AWS technology stack, including Amazon Bedrock and/or SageMaker, API Gateway, ECS or EKS, ECR, S3, IAM, Secrets Manager, KMS, CloudWatch, and related services.
• Strong experience containerizing Python-based applications and APIs using Docker and deploying them into scalable ECS, EKS, or Kubernetes environments.
• Hands-on experience integrating applications with Databricks REST APIs, preferably including the Genie Conversation API, SQL Statement Execution API, SQL Warehouses, OAuth authentication, and Unity Catalog-governed data.
• Experience building API-based chatbot or agent-orchestration services using Python and frameworks such as FastAPI, Flask, LangChain, LangGraph, or comparable technologies.
• Experience implementing routing across structured-data, RAG, and hybrid question-answering workflows.
• Experience connecting AI applications to vector stores such as Amazon OpenSearch Serverless, Bedrock Knowledge Bases, PostgreSQL/pgvector, or Databricks Vector Search.
• Experience developing document-ingestion pipelines for SharePoint, S3, file repositories, or other enterprise knowledge sources, including extraction, chunking, embeddings, metadata enrichment, synchronization, and deletion handling.
• Experience implementing secure token handling, OAuth/OIDC flows, service-principal authentication, secrets management, least-privilege IAM, and server-side session management.
• Experience creating CI/CD pipelines for containerized AI applications, including automated testing, vulnerability scanning, image promotion, deployment, rollback, and configuration management.
• Experience load-testing and scaling chatbot or model-enabled applications based on concurrent users, request volume, model latency, token utilization, and downstream API constraints.
• Experience implementing production observability, including application logging, distributed correlation IDs, metrics, tracing, API latency monitoring, model usage monitoring, alerting, and audit-log integration.
• Ability to troubleshoot issues spanning application code, Docker containers, AWS networking, IAM, Databricks APIs, SQL execution, model endpoints, and vector retrieval.
• Ability to implement guardrails that limit data returned to the model, restrict the application to approved Databricks views, prevent credentials from reaching the browser, and preserve end-to-end auditability.

Preferred qualifications:

• Experience deploying applications within the War Data Platform, formerly Advana, or integrating with WDP-hosted Databricks services.
• Experience supporting AWS GovCloud, DoD IL4/IL5, CUI, or other highly regulated environments.
• Experience with Databricks Genie, Unity Catalog, Databricks Vector Search/AI Search, and user-level OAuth integrations.
• Experience integrating reusable chatbot widgets or APIs into multiple websites, such as PBIS, Jupiter Homepage, Community Portal, or similar enterprise applications.
• Experience with Terraform, CloudFormation, AWS CDK, Helm, Kubernetes, and Git-based CI/CD platforms.

Infopact is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other characteristic protected by law. We strongly encourage veterans — including those with technical and operational occupational specialties — to apply.