JPC - 204698 - AI Engineer

Job Title: AI-Focused Software Engineer — Video Insights About the Role The Video Insights team is hiring two AI-focused Software Engineers to design, build, and deploy AI-powered tools and workflows that make our data analysts, data engineers, and QA teams more effective. This is a hands-on engineering role focused on building practical solutions, not research. You'll work directly with the team to understand their workflows, identify high-impact automation opportunities, and ship tools that reduce manual effort across the Video Insights ecosystem. This role sits at the intersection of software engineering and applied AI. You'll build AI agents, develop MCP (Model Context Protocol) servers, create context-aware tooling, and support the team's adoption of AI across ETL development, Tableau reporting, analytics tagging, test validation, and project management workflows. What You'll Do Process Optimization · Eliminate manual bottlenecks across the team's reporting, tagging, and testing workflows · Build AI agents that assist at each stage of the development lifecycle, from requirements and architecture review through coding, testing, debugging, and deployment · Reduce onboarding friction by capturing tribal knowledge into structured, searchable formats that new team members and AI tools can use immediately Automation · Automate repetitive tasks across analytics requirements gathering, data validation, job monitoring, and Tableau reporting · Build agents that detect pipeline failures, read logs, surface root causes, and recommend fixes · Create reusable prompt templates, steering files, and workspace configurations that standardize AI behavior across the team Tool Integration · Develop and maintain MCP servers that connect AI tools to the Video Insights data ecosystem, giving agents real context about our data, schemas, and business logic · Integrate AI tooling with the team's existing platforms (Jira, Confluence, Gitlab, Athena, Tableau) to reduce context switching Cost & Performance Tuning · Develop data quality monitoring agents that detect anomalies and assess downstream lineage impact · Automate data cleanup and resource optimization workflows · Build guardrails into AI-assisted query tools to prevent expensive or unbounded operations Software Engineering · Build internal tools and applications using modern web technologies (TypeScript, React, Node.js, Python) · Develop APIs and backend services that power AI agent workflows and connect to internal data platforms · Write clean, tested, documented code — this team hasn't had dedicated SWEs before, so you'll be setting the engineering standards · Work within AWS infrastructure (Athena, EMR, S3, Lambda) and integrate with the team's existing data stack

What We're Looking For

Required · 3+ years of software engineering experience with production applications (TypeScript/JavaScript, Python, or similar) · Active AWS certification and demonstrated knowledge of AWS services · Hands-on experience building with LLMs — prompt engineering, agent frameworks, tool-use patterns, or RAG systems · Familiarity with the Model Context Protocol (MCP) or similar agent-tool integration patterns · Experience with SQL and data platforms (Athena, Spark, or equivalent) · Strong software debugging skills, including ability to diagnose issues across distributed systems, data pipelines, and AI agent workflows · Ability to design thorough test cases and support reliability testing across the tools and agents you build · Strong written and verbal communication skills · Ability to manage your own development work effectively · Ability to translate non-technical team needs into working software Preferred · Experience building knowledge graphs, context graphs, or semantic layers for enterprise data · Familiarity with Tableau, data visualization tools, or BI platform APIs · Background in data engineering or analytics, understanding ETL pipelines, data quality, and validation workflows · Experience with CI/CD, Gitlab, and infrastructure-as-code · Familiarity with Jira APIs, Confluence, or project management tool integrations · Experience with job monitoring, log analysis, or operational alerting systems

Why This Role Is Different This isn't a traditional SWE role in a product engineering org. You'll be embedded in a data-driven team that already uses AI daily and needs someone to turn those experiments into reliable, scalable tools. The team has active use cases in SQL optimization, test automation, and documentation. What's missing is the engineering muscle to build the connective tissue: the MCP servers, the agents, and the internal tools that make AI work reliably at team scale.

Required Skills : Cannot be experimentation only, Data Science folks working in notebooks and developing only POCs. The production experience and Software fundamentals are critical to the role. Needs an AWS Certification: try to ID candidates with an active Cloud Practitioner/Solution Architect (prefers the core cloud certs over the AI/ML specific ones), but we can explore having them obtain it once they join Client as well. Mentioned that MCP server experience is limited in the market - if they have familiarity in MCP, with experience in broader integrations or CLI-based extensions to connect to external sources, that is okay. LLMs, RAG, agents and agent orchestration (LangChain, Crew AI, etc.) - would recommend starting here. Software development skills - UIs with React/Typescript, Node.js, Python - she was not sure if both Node.js and Python were being used on the API side. Often times these products use Python/FastAPI. Needs deep experience in AWS - i.e. S3, EC2, EMR, Lambdas, Athena Containerization, CI/CD desired. Basic Qualification : Additional Skills :

Background Check : Yes Drug Screen : Yes

Notes : Selling points for candidate : Project Verification Info :"The information provided below is for Client Systems AV use only and is not to be distributed publicly, or to any third party. Any distribution of the below information will result in corrective action from Client Systems Vendor Management.

MSA: Blanket Approval Received Client Letter: Will Provide" Exclusive to Client :Yes Face to face interview required :No Candidate must be local :No Candidate must be authorized to work without sponsorship ::No Interview times set : :No Type of project : Master Job Title : Branch Code :