{"id":104796,"url":"https://alion.io/job/ahead-senior-ai-engineer-ai-services","title":"Senior AI Engineer, AI Services","company":{"id":3614,"name":"AHEAD","domain":"ahead.com","url":"https://alion.io/company/ahead","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":74,"open_postings":51,"ghost_share":0,"stale_share":0.824,"repost_share":0,"time_to_fill_p50_days":72,"computed_at":"2026-10-21T05:46:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":200000,"max":250000,"currency":"USD","period":"year","gross":null,"usd_annual":250000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon EventBridge","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Celery","optional":false},{"name":"CI/CD","optional":false},{"name":"Cortex","optional":false},{"name":"CrewAI","optional":false},{"name":"Databricks","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Function Calling","optional":false},{"name":"Jira","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"n8n","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"ServiceNow","optional":false},{"name":"SharePoint","optional":false},{"name":"Snowflake","optional":false},{"name":"Structured Outputs","optional":false},{"name":"PostgreSQL","optional":true},{"name":"Prometheus","optional":true}],"status":"live","first_seen_at":"2025-12-04T22:14:58Z","employer_posted_date":"2025-12-04","last_verified_at":"2026-10-21T09:36:14Z","board_verified":true,"closed_at":null,"days_open":320,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":320},"description":"AHEAD is seeking a Senior AI Engineer, AI Services to help design, build, and deploy enterprise-grade AI solutions for our clients.\nThis is a hands-on technical consulting role for someone who can translate ambiguous business and technical needs into practical, scalable, and secure AI solutions. You will work alongside client technology and business stakeholders, AHEAD architects, and delivery teams to understand requirements, shape solution designs, develop and integrate AI capabilities, and help move initiatives from prototype to production and measurable business value.\nThe ideal candidate brings strong software engineering fundamentals, applied AI and machine learning fluency, and the ability to make sound technical decisions in complex enterprise environments. You should be comfortable contributing to architecture discussions, evaluating trade-offs, developing proof-of-concept solutions, supporting production implementations, and communicating technical concepts clearly to both technical and non-technical audiences.\nSuccess in this role requires credibility with engineers, data scientists, architects, platform teams, security stakeholders, and business leaders. You will be expected to take ownership of assigned technical workstreams, collaborate effectively across teams, proactively identify risks and dependencies, and contribute to high-quality client outcomes. You will also help share knowledge, establish repeatable delivery practices, and mentor less-experienced team members.\nThis role is well suited for candidates with backgrounds in applied AI consulting, machine learning engineering, AI solution architecture, technical product development, data science engineering, or advanced analytics engineering environments. Candidates should be energized by solving real-world client problems and turning emerging AI capabilities into reliable, maintainable solutions that create business impact.\nKey Responsibilities\n Solution Development & Deployment \nBuild and deploy multi-agent systems using frameworks such as LangChain, LangGraph, Autogen, CrewAI, and LlamaIndex. \nDevelop custom agents for document processing, workflow automation, SDLC acceleration, data analysis, and business process orchestration. \nIntegrate LLMs, SLMs, embeddings, and retrieval pipelines (Pinecone, Elasticsearch, Snowflake Cortex, pgvector) \nCreate and operate LLM/ML endpoints, agent memory/state stores, and event-driven triggers. \nImplement reusable components that become part of AHEAD’s agent library and client solution accelerators \n Enterprise Integration & Workflow Automation \nBuild real-time and batch workflows using Python, Kafka, EventBridge, Airflow, Snowflake, S3, n8n, AWS Batch, and similar tools. \nConnect agents to enterprise systems (SharePoint, Salesforce, ServiceNow, Jira, Oracle, databases, APIs). \nImplement RAG, tool-calling, function calling, and structured output pipelines for production-ready agentic tasks. \nEnsure robust data transformations, validation, and versioning for downstream agent workflows. \n Quality, Observability & Reliability \nImplement monitoring, metrics, and guardrails for multi-agent systems (timeouts, retries, constraints, circuit breakers). \nBuild automated testing for agent behaviors, prompts, ETL/batch jobs, and model outputs. \nParticipate in incident reviews, debugging multi-agent flows, and ensuring predictable performance. \nClient Collaboration & Delivery Excellence \nWork closely with client stakeholders to understand use cases, pain points, and success criteria. \nTranslate business needs into technical agent designs and execution roadmaps. \nParticipate in agile ceremonies, demos, and working sessions with client teams. \nContribute to proposals, SOWs, architecture diagrams, and client documentation when needed. \nSecurity, Governance & Compliance \nApply enterprise standards for data security, access control, auditing, model governance, and safe AI usage. \nEmbed monitoring, lineage, PII handling, and policy constraints into agentic flows. \nMentorship & Internal Development \nCoach junior engineers on agent design patterns, RAG, orchestration, and clean engineering practices. \nContribute to internal best practices, reference architectures, and reusable components. \nSupport onboarding of new engineers and help scale AHEAD's agentic engineering community. \nQualifications\n Required \nStrong Python engineering background, including async patterns, APIs, and event-driven design. \nHands-on experience with multi-agent frameworks (LangGraph, Autogen, CrewAI, LangChain, etc.). \nDemonstrated ability to build production ETL, orchestration, or workflow automation pipelines (Kafka, EventBridge, Airflow, Celery, n8n, AWS services). \nExperience with vector DBs and retrieval pipelines (Pinecone, pgvector, Elasticsearch, LlamaIndex). \nFamiliarity with MLOps, observability, CI/CD, containerization, and model deployment patterns. \nStrong documentation habits and comfort working in fast-paced agile environments. \nExperience integrating with enterprise systems or APIs in production. \nPreferred \nExperience with Snowflake Cortex, Databricks Mosaic, NVIDIA NIMs, or similar AI platform components. \nExperience operating agentic systems at scale, including safety constraints and system-level debugging. \nExperience in consulting, client-facing engineering, or co-development models. \n Success Metrics & Environment \nDelivery of reliable, scalable agentic solutions that measurably improve client outcomes. \nHigh client satisfaction, repeat demand, and strong cross-functional collaboration. \nConsistent contribution to reusable accelerators and internal knowledge base. \nPredictable delivery cadence with strong engineering quality and observability. \nVisible growth of AHEAD's reputation for agentic AI expertise.","description_format":"text","description_chars":5795,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","Managed IT Services (MSP)","AI Consulting & Integration","Cloud Consulting & Migration"],"lifecycle":[{"event":"open","at":"2025-12-04T22:14:58Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 23 · green card filings: 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