{"id":953373,"url":"https://alion.io/job/paralucent-agentic-ai-platform-engineer-pl862","title":"Agentic AI Platform Engineer (PL862)","company":{"id":685853,"name":"Paralucent","domain":"paralucent.com","url":"https://alion.io/company/paralucent","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Recruitee","truth_index":{"grade":"C","score":63,"open_postings":23,"ghost_share":0.609,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":27,"computed_at":"2026-11-02T06:13:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":76000,"max_usd":165000,"period":"year","method":"role_country_seniority_unknown","sample_n":229},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"C#","optional":false},{"name":"Function Calling","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"JavaScript","optional":false},{"name":"LLM","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TypeScript","optional":false},{"name":"Agile","optional":true},{"name":"AutoGen","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"Azure DevOps","optional":true},{"name":"CI/CD","optional":true},{"name":"Confluence","optional":true},{"name":"CrewAI","optional":true},{"name":"Embeddings","optional":true},{"name":"Git","optional":true},{"name":"GitHub","optional":true},{"name":"Jira","optional":true},{"name":"LangChain","optional":true},{"name":"OpenAI","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"Semantic Kernel","optional":true},{"name":"ServiceNow","optional":true}],"status":"live","first_seen_at":"2026-07-13T13:06:20Z","employer_posted_date":"2026-07-13","last_verified_at":"2026-11-02T07:05:18Z","board_verified":true,"closed_at":null,"days_open":111,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":111},"description":"Location: Toronto, ON\nWork Model: Hybrid - 2 days/week downtown Toronto\n# of roles: 2\n\nParalucent is seeking an experienced Agentic AI Platform Engineer to join our team and support a major client in the banking sector. In this role, you will be responsible for the hands-on design, development, integration, and execution of AI-driven initiatives focused on agentic AI, cloud platforms, enterprise workflows, and scalable platform modernization.\nThis opportunity is ideal for a technically strong engineer who can translate delivery plans, architecture direction, business requirements, and platform strategy into working solutions. You will work closely with the Delivery Manager, architects, technical leads, client stakeholders, and cross-functional teams to build, test, and deploy agentic AI-enabled capabilities within a complex enterprise environment involving cloud technologies, enterprise integrations, governance requirements, and production-readiness expectations.\nThe successful candidate will play a critical role in turning strategy and technical vision into practical, secure, scalable, and measurable AI-enabled solutions.\nKey Responsibilities\n\nAgentic AI Solution Development\nDesign, develop, and implement agentic AI workflows, AI-enabled services, prototypes, and production-ready platform components.\n\nBuild solutions that support enterprise workflows, business process transformation, intelligent automation, and human-in-the-loop execution.\n\nImplement agentic patterns involving task planning, tool/API usage, workflow orchestration, validation, exception handling, and escalation.\n\nPlatform Engineering & Cloud Development\nDevelop cloud-native applications, services, APIs, and integrations using AWS and/or Azure.\n\nBuild reusable platform components, connectors, services, and integration patterns that support scalable AI platform delivery.\n\nPartner with architects and technical leads to ensure solutions align with enterprise architecture, security, cloud, and operational standards.\n\nAI / LLM Implementation\nImplement solutions using Artificial Intelligence (AI), Generative AI (GenAI), Large Language Models (LLMs), and agentic AI frameworks or patterns.\n\nDevelop prompt strategies, structured outputs, tool-calling workflows, retrieval-augmented generation patterns, and AI validation approaches.\n\nSupport accuracy, reliability, auditability, and safe execution through testing, guardrails, logging, and human review patterns.\n\nEnterprise Integration & Workflow Automation\nIntegrate AI-enabled workflows with enterprise applications, APIs, databases, document repositories, and workflow platforms.\n\nBuild automation and integration components that connect AI capabilities to business processes and operational systems.\n\nSupport secure access, identity, data flow, logging, monitoring, and compliance-aware implementation within a regulated enterprise environment.\n\nDelivery Execution & Technical Collaboration\nWork closely with the Delivery Manager to execute against delivery plans, milestones, sprint priorities, and release timelines.\n\nBreak down technical requirements into tasks, estimates, dependencies, and implementation steps.\n\nParticipate in discovery, design, development, pilot, release, and production-readiness activities with clear technical accountability.\n\nQuality, Testing & Production Readiness\nWrite clean, maintainable, secure, and well-documented code.\n\nDevelop unit tests, integration tests, validation routines, and AI output evaluation approaches.\n\nSupport deployment, release readiness, operational handoff, troubleshooting, root cause analysis, and continuous improvement.\n\nRequirements\nRequired Qualifications\nProven experience as a Software Developer, AI Engineer, Platform Engineer, Cloud Developer, Full-Stack Developer, or similar hands-on technical role within complex enterprise technology environments.\n\nDemonstrated experience designing and building software solutions, APIs, integrations, workflow automations, or platform components.\n\nExperience developing solutions within technically complex environments involving cloud platforms such as AWS and/or Azure, enterprise integrations, and modern software delivery practices.\n\nPractical experience or strong exposure to Artificial Intelligence (AI), Generative AI (GenAI), Agentic AI, LLM-enabled applications, intelligent automation, or AI-assisted workflow solutions.\n\nStrong programming experience with languages such as Python, TypeScript, JavaScript, Java, C#, or similar modern development languages.\n\nAbility to translate business requirements, architecture direction, and delivery plans into working technical solutions.\n\nExperience working with APIs, databases, cloud services, enterprise applications, document repositories, or workflow platforms.\n\nStrong understanding of software development lifecycle practices, including design, development, testing, deployment, and support.\n\nAbility to effectively partner with Delivery Managers, architects, technical leads, business analysts, QA teams, and client stakeholders.\n\nStrong problem-solving, communication, and execution skills in ambiguous, fast-moving enterprise environments.\n\nPreferred Qualifications\nExperience building or implementing agentic AI applications using frameworks or patterns such as Semantic Kernel, LangChain, AutoGen, CrewAI, Azure AI Foundry, AWS Bedrock Agents, OpenAI Assistants, or similar technologies.\n\nExperience supporting initiatives involving Artificial Intelligence (AI), Generative AI (GenAI), Agentic AI, intelligent automation, workflow modernization, or platform modernization programs.\n\nExperience working within financial services, banking, or other highly regulated enterprise environments.\n\nExposure to lending operations, servicing, workflow management, process execution, or enterprise operations is considered an asset but is not required.\n\nFamiliarity with retrieval-augmented generation, embeddings, vector databases, document processing, knowledge retrieval, and enterprise search patterns.\n\nFamiliarity with secure software development, cloud security, identity/access management, auditability, and compliance-aware delivery.\n\nExperience with DevOps practices, CI/CD pipelines, Git-based workflows, infrastructure-as-code, containers, and cloud deployment patterns.\n\nFamiliarity with Jira, ServiceNow, Confluence, Azure DevOps, GitHub, or similar delivery and operational tooling.\n\nExperience supporting pilots, proofs of concept, MVPs, production deployments, platform stabilization, and operational transitions.\n\nCore Competencies\nAgentic AI Engineering\n\nSoftware Development & Platform Execution\n\nCloud Platform Development - AWS and/or Azure\n\nAI / GenAI / LLM Implementation\n\nAPI & Enterprise Integration\n\nWorkflow Automation\n\nPrompt Engineering & AI Orchestration\n\nRetrieval-Augmented Generation & Knowledge Retrieval\n\nSecure, Reliable, Production-Ready Engineering\n\nTechnical Problem Solving\n\nAgile Delivery Execution\n\nQuality Engineering & Testing\n\nRelease Readiness & Operational Handoff\n\nCross-Functional Collaboration\n\nCommunication, Ownership & Delivery 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