{"id":3308993,"url":"https://alion.io/job/fulcrum-digital-forward-deployement-engineer","title":"Forward Deployement Engineer","company":{"id":2008418,"name":"Fulcrum Digital","domain":"fulcrumdigital.com","url":"https://alion.io/company/fulcrumdigital","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"OpenAI","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"ServiceNow","optional":false},{"name":"SharePoint","optional":false},{"name":"Weaviate","optional":false}],"status":"live","first_seen_at":"2026-10-26T23:53:48Z","employer_posted_date":null,"last_verified_at":"2026-10-26T23:53:48Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"Key Responsibilities\n\nBusiness Discovery & Solution Design\n\nPartner with business leaders, product owners, and operational teams to identify high-value AI use cases. \n\nConduct workshops and discovery sessions to understand workflows, pain points, and business objectives. \n\nTranslate business requirements into scalable AI and automation solutions. \n\nDefine MVP scope, success criteria, KPIs, and implementation roadmaps. \n\nAI Engineering & Development\n\nDesign, build, and deploy Generative AI and Agentic AI solutions. \n\nDevelop RAG (Retrieval Augmented Generation) applications leveraging enterprise knowledge sources. \n\nBuild intelligent agents capable of automating underwriting, claims, customer service, IT support, and operational workflows. \n\nIntegrate AI services with enterprise platforms, APIs, databases, SharePoint, ServiceNow, CRM, and document repositories. \n\nPlatform Integration & Deployment\n\nDeploy AI models and applications into Azure cloud environments. \n\nBuild secure and compliant integrations aligned with enterprise governance standards. \n\nConfigure monitoring, observability, logging, and performance metrics. \n\nSupport production deployment and operational readiness activities. \n\nProduction Ownership\n\nOwn the end-to-end success of deployed AI solutions. \n\nTroubleshoot production issues and optimize model performance. \n\nImprove solution accuracy, latency, scalability, reliability, and cost efficiency. \n\nEstablish feedback mechanisms and continuous improvement processes. \n\nStakeholder Engagement\n\nCollaborate with business executives, architects, developers, data engineers, and security teams. \n\nPresent solution architectures, progress updates, and business value realization metrics. \n\nFacilitate adoption and change management activities. \n\nMentor internal teams on AI engineering best practices. \n\nInnovation & Value Creation\n\nContinuously identify new AI opportunities within underwriting, claims, risk management, customer service, and corporate operations. \n\nPrototype emerging AI capabilities and demonstrate proof-of-value. \n\nRecommend reusable AI assets, frameworks, and accelerators. \n\nSupport strategic AI roadmap development and future-state architecture. \n\nRequired Qualifications\n\nTechnical Skills\n\nStrong proficiency in Python and modern software engineering practices. \n\nHands-on experience with Generative AI technologies, LLMs, and AI agents. \n\nExperience building RAG pipelines using vector databases and enterprise content repositories. \n\nStrong knowledge of Azure AI services, Azure OpenAI, Azure Functions, and cloud-native development. \n\nExperience with REST APIs, microservices, containers, and CI/CD pipelines. \n\nFamiliarity with model deployment, monitoring, evaluation frameworks, and MLOps practices. \n\nAI & Agent Frameworks\n\nExperience with one or more: \nLangChain \n\nLangGraph \n\nSemantic Kernel \n\nAutoGen \n\nCrewAI \n\nPrompt Engineering and Evaluation Frameworks \n\nVector Databases (Pinecone, Azure AI Search, Weaviate, 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