{"id":3699329,"url":"https://alion.io/job/disa-ai-analyst","title":"AI Analyst","company":{"id":1972635,"name":"DISA","domain":"disa.com","url":"https://alion.io/company/disa-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":97,"open_postings":3,"ghost_share":0,"stale_share":0.333,"repost_share":0,"time_to_fill_p50_days":15,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Analytics","role_family":"Analytics","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"API Gateway","optional":false},{"name":"ASP.NET Core","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Bicep","optional":false},{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Hallucination","optional":false},{"name":"JavaScript","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenSearch","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"Rest API","optional":false},{"name":"Terraform","optional":false},{"name":"TypeScript","optional":false},{"name":"Copilot Studio","optional":true},{"name":"FinOps","optional":true},{"name":"Human-in-the-Loop","optional":true},{"name":"Machine Learning","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"Power Automate","optional":true},{"name":"UiPath","optional":true}],"status":"live","first_seen_at":"2026-11-03T18:58:47Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-04T01:14:59Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"DISA Global Solutions is an industry-leading safety and compliance solutions provider with customers across the Globe since 1986 and more than 1,200+ Team members across more than 30 locations. When you join the DISA Team, you join an industry leader that more than 30% of fortune 500 companies use. With a rich history of IT innovation, we have more than 55,000 customers and complete more than 10 million orders each year.\nDISA is proud to be a “Top Workplaces” award winner across multiple locations in 2023. We offer competitive pay, a robust benefits package, and an exciting place to work. We have a collaborative and team-oriented culture with numerous opportunities for career advancement. We host monthly appreciation events, and our internal learning and development team provides the resources for employees to engage in continuing education and training.\nRole Overview\nWe are seeking a versatile AI Engineer to design, architect, build, and operationalize secure, scalable, and production-grade applications with AI embedded within business services. The role is intentionally broad and fluid: the engineer will work across front-end, back-end, APIs, cloud AI services, and intelligent automation based on evolving business priorities. In addition to Generative AI solutions, the engineer is expected to build RPA bots enhanced with AI when automation opportunities arise.\nPrimary Focus: Full-stack AI applications, Generative AI, RAG, agentic solutions, AI document processing, intelligent automation and RPA, cloud AI architecture, secure integration, and production operations.\nKey Responsibilities\nDesign and build end-to-end enterprise applications with AI capabilities integrated into business services and workflows.\nDevelop responsive front-end applications using React and create secure back-end services using C#/.NET Core, Python, and REST APIs.\nDesign end-to-end enterprise AI and Generative AI solutions aligned with functional, security, integration, performance, availability, and cost requirements.\nCreate high-level and detailed solution architectures, architecture decision records, data flows, API contracts, deployment patterns, and technical specifications.\nBuild Retrieval-Augmented Generation (RAG), AI agents, copilots, document intelligence, conversational AI, and intelligent workflow solutions.\nBuild RPA bots and intelligent automation workflows, integrating AI capabilities such as document understanding, classification, extraction, summarization, and decision support where relevant.\nArchitect and implement Azure-based solutions using Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure AI Document Intelligence, Azure Functions, Service Bus, API Management, Storage, and AKS.\nArchitect and implement AWS-based solutions using Amazon Bedrock, Bedrock Agents and Knowledge Bases, Lambda, S3, OpenSearch, API Gateway, ECS, or EKS.\nEvaluate foundation models and select models based on quality, latency, safety, data residency, throughput, and cost.\nDevelop secure REST APIs, microservices, and event-driven processing components using C#/.NET Core and Python.\nImplement prompt management, grounding, structured outputs, guardrails, content safety, evaluation, observability, and hallucination-reduction controls.\nBuild CI/CD and Infrastructure-as-Code pipelines for repeatable provisioning, testing, and deployment across environments.\nPartner with product, engineering, security, architecture, compliance, and business teams to move solutions from discovery and proof of concept into production.\nConduct design reviews, troubleshoot complex technical issues, document engineering decisions, and mentor junior engineers.\nRequired Technical Skills\nStrong full-stack application development experience, including React, JavaScript/TypeScript, C#/.NET Core, Python, REST APIs, and service integration.\nExperience designing applications in which AI capabilities are embedded within user-facing and back-end business services rather than delivered only as standalone models or prototypes.\nStrong experience in AI solution design and architecture, including cloud-native, microservices, event-driven, API-led, and containerized patterns.\nHands-on experience with Generative AI, LLMs, prompt engineering, embeddings, vector search, RAG, tool/function calling, and agent orchestration.\nPractical experience with Azure AI services and AWS Bedrock services in enterprise solution delivery.\nHands-on experience building RPA bots and workflow automations using a leading RPA platform, with the ability to integrate bots with APIs, enterprise applications, and AI services.\nExperience with FastAPI or similar API frameworks, ASP.NET Core Web API, OAuth 2.0, JWT, managed identities, RBAC, secrets management, and secure networking.\nExperience with relational and NoSQL data stores, vector databases, caching, object storage, and search platforms.\nWorking experience with Docker, Kubernetes, Git, Azure DevOps or GitHub Actions, and Terraform, Bicep, or CloudFormation.\nUnderstanding of AI evaluation, model monitoring, prompt/version management, telemetry, responsible AI, privacy, and governance.\nAbility to work across changing priorities and select the appropriate engineering approach for AI applications, full-stack development, API integration, or RPA automation.\nQualifications\nBachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline.\n4-6 years of professional software engineering or AI engineering experience.\nDemonstrated experience designing and delivering full-stack applications and AI solutions on Azure and/or AWS.\nExperience taking applications, AI solutions, or automation bots through design, development, testing, security review, deployment, monitoring, and operational support.\nStrong analytical, documentation, stakeholder communication, and technical problem-solving skills.\nPreferred Experience\nAzure AI Engineer Associate, Azure Solutions Architect, AWS Solutions Architect, AWS Machine Learning, or relevant application development certification.\nExperience with Microsoft Copilot Studio, Azure AI Foundry Agent Service, Amazon Bedrock Agents, or multi-agent frameworks.\nExperience with React-based enterprise applications, ASP.NET Core services, API gateways, and modern authentication patterns.\nExperience with Power Automate Desktop, UiPath, Automation Anywhere, or equivalent RPA platforms, including AI-assisted automation use cases.\nExperience with document processing, voice AI, human-in-the-loop review, workflow orchestration, or enterprise automation.\nKnowledge of FinOps practices and cost optimization for AI workloads.\nExperience working in regulated or security-conscious enterprise environments.\nSuccess Measures\nApplications and architectures are secure, supportable, scalable, and aligned with enterprise standards.\nAI capabilities are effectively integrated into business services and deliver measurable quality, reliability, latency, and cost performance.\nRPA bots are reliable, maintainable, auditable, and appropriately enhanced with AI where it improves business outcomes.\nProofs of concept are converted into production-ready implementations with complete operational controls.\nTechnical documentation, testing evidence, deployment automation, and monitoring are complete and reusable.\nRisks, assumptions, dependencies, and design trade-offs are clearly communicated to stakeholders.\nDISA Global Solutions is an equal opportunity employer committed to creating a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, caste, gender, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, marital status, or any other legally protected status. 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