{"schemaVersion":"jobsearcher.job.v1","id":"6289d87c5c1f9bbef796d3ea","url":"https://jobsearcher.com/jobs/6289d87c5c1f9bbef796d3ea","canonicalUrl":"https://jobsearcher.com/jobs/6289d87c5c1f9bbef796d3ea","title":"Engineering - Agentic AI Engineer (Junior)","description":"Aline is the bridge between senior care and technology, built to strengthen connection where it matters most. Our all-in-one platform brings together sales, marketing, operations, and engagement tools, empowering senior living communities to work smarter, communicate clearly, and deliver care with heart.\nRooted in industry expertise and born from the merger of leading solutions, Aline serves as a unifying force across the senior care space. We help communities across the country streamline processes, enhance resident and family engagement, and stay aligned through every stage of care. That’s why everything we build is designed to support stronger collaboration, seamless workflows, and more meaningful experiences for residents, families, and care teams alike.\n\nWe are looking for a motivated and technically sharp Junior Agentic (AI) Engineer to join Aline’s engineering team. This entry-level role is designed for engineers with 1–5 years of experience — or strong recent graduates — who have a genuine interest in building production-grade agentic systems for enterprise workflows. You will work directly with customers and cross-functional teams to design, build, and ship AI-powered features that improve outcomes for senior living communities. From architecting multi-agent workflows to owning the retrieval and eval stack, you will gain hands-on experience across the full AI product lifecycle — with a focus on reliability, compliance, and measurable impact.\nResponsibilities\nAgentic Systems & Orchestration\n\nBuild and deploy agentic systems for enterprise workflows — design and implement AI agents (and multi-agent systems) that reason and retrieve data across complex business processes and take action in enterprise systems.\nDesign and ship multi-step agentic systems — planner/executor, tool-using, multi-agent, and human-in-the-loop — for use cases including onboarding, underwriting, case review, and continuous monitoring.\nDesign orchestration, reasoning, and workflows — architect how agents plan, use tools, and coordinate across complex, multi-step processes.\nArchitect agent graphs in LangGraph (or comparable frameworks — CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks.\nExpose agents to production systems via well-typed tools and MCP servers; treat the tool surface area as a product.\nFull-Stack Implementation & Integrations\n\nOwn full-stack implementation and integrations — build across LLMs, APIs, backend systems, and lightweight UIs to deliver complete, working solutions.\nBuild and own the retrieval layer powering our agents: chunking strategies, hybrid search (vector + keyword), reranking, and grounded citation.\nDesign and optimize embedding pipelines and vector indexes using pgvector and OpenSearch.\nEvaluation, Safety & Reliability\n\nDevelop agentic harnesses to accelerate development — create evaluation frameworks, toolchains, and workflows that enable rapid iteration and improve system reliability.\nOwn the eval stack: curate golden sets, maintain offline regression suites, implement LLM-as-judge, and run online A/B and shadow evals.\nEnsure reliability, safety, and production readiness — implement guardrails, validation logic, and fallback mechanisms to ensure consistent and trustworthy behavior in production.\nTechnology Stack\nLanguages\nPython, Node.js, TypeScript Agent / LLM Frameworks LangGraph, LangChain, Claude Agent SDK, MCP, OpenAI SDK\nModels\nAnthropic Claude, OpenAI, open-weight where appropriate Retrieval & Data PostgreSQL, pgvector, OpenSearch, Kafka, Redshift, Redis\nInfrastructure\nAWS, Kubernetes (EKS), ArgoCD, Terraform Evals & Observability LangSmith / Langfuse / Braintrust, DataDog\n\nQualifications\nEducation & Experience\n\nBachelor's degree in Computer Science, Data Science, AI/ML, or related field, or equivalent practical experience through projects, research, internships, or professional work.\n1–5+ years in software engineering (full-stack or backend), or a strong recent graduate with demonstrable project or internship experience at equivalent depth.\nFamiliarity with LLMs or AI-based systems.\nInternship or research experience in a production AI or data-intensive environment is a strong plus.\nRequired Technical Skills\n\nProficiency in Python; comfortable with NumPy, Pandas, and Scikit-learn.\nHands-on experience with at least one LLM framework: LangGraph, LangChain, Claude Agent SDK, or OpenAI SDK.\nUnderstanding of RAG architecture: embedding models, vector databases, hybrid search, and reranking.\nFamiliarity with prompt engineering best practices and awareness of LLM failure modes (hallucination, injection, drift).\nWorking knowledge of SQL and relational databases (PostgreSQL, MySQL, or similar).\nFamiliarity with Git version control and Agile/Scrum practices.\nPreferred\n\nExperience with agent systems, orchestration frameworks (LangGraph, CrewAI,AutoGen), or AI tooling.\nExposure to MCP (Model Context Protocol) or building typed tool interfaces for LLM agents.\nExperience with eval frameworks (LangSmith, Langfuse, Braintrust) or building LLM-as-judge pipelines.\nFamiliarity with cloud platforms — AWS preferred (Azure, GCP also considered).\nExposure to Kubernetes, Docker, ArgoCD, or Terraform for AI service deployment.\nExposure to data compliance requirements: SOC 2, GDPR, CCPA, HIPAA.\nSoft Skills\n\nStrong analytical mindset with intellectual curiosity about agents, evals, and production AI behavior.\nThis role includes regular interaction with customers to understand workflows, validate solutions, and gather feedback.\nClear written and verbal communication; able to explain LLM behavior and tradeoffs to diverse audiences.\nSelf-motivated, detail-oriented, and comfortable operating in a fast-moving environment.\nGenuine interest in the mission of improving outcomes in senior care through responsible AI.\nCandidates should demonstrate experience building LLM-powered applications, evaluating agent behavior, and working through the full development lifecycle from prototype to production.\nThis job description is intended as a summary of the primary responsibilities and qualifications for this position. It is not intended as an all-inclusive list of duties or qualifications that may be required now or in the future.\n\nVisa Sponsorship: Aline is not able to provide visa sponsorship at this time. Applicants must be authorized to work in the United States without sponsorship.","company":"Aline","rawCompany":"aline","city":"Remote","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-08-04T18:38:10.635Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Engineering - Agentic AI Engineer (Junior)","description":"Aline is the bridge between senior care and technology, built to strengthen connection where it matters most. Our all-in-one platform brings together sales, marketing, operations, and engagement tools, empowering senior living communities to work smarter, communicate clearly, and deliver care with heart.\nRooted in industry expertise and born from the merger of leading solutions, Aline serves as a unifying force across the senior care space. We help communities across the country streamline processes, enhance resident and family engagement, and stay aligned through every stage of care. That’s why everything we build is designed to support stronger collaboration, seamless workflows, and more meaningful experiences for residents, families, and care teams alike.\n\nWe are looking for a motivated and technically sharp Junior Agentic (AI) Engineer to join Aline’s engineering team. This entry-level role is designed for engineers with 1–5 years of experience — or strong recent graduates — who have a genuine interest in building production-grade agentic systems for enterprise workflows. You will work directly with customers and cross-functional teams to design, build, and ship AI-powered features that improve outcomes for senior living communities. From architecting multi-agent workflows to owning the retrieval and eval stack, you will gain hands-on experience across the full AI product lifecycle — with a focus on reliability, compliance, and measurable impact.\nResponsibilities\nAgentic Systems & Orchestration\n\nBuild and deploy agentic systems for enterprise workflows — design and implement AI agents (and multi-agent systems) that reason and retrieve data across complex business processes and take action in enterprise systems.\nDesign and ship multi-step agentic systems — planner/executor, tool-using, multi-agent, and human-in-the-loop — for use cases including onboarding, underwriting, case review, and continuous monitoring.\nDesign orchestration, reasoning, and workflows — architect how agents plan, use tools, and coordinate across complex, multi-step processes.\nArchitect agent graphs in LangGraph (or comparable frameworks — CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks.\nExpose agents to production systems via well-typed tools and MCP servers; treat the tool surface area as a product.\nFull-Stack Implementation & Integrations\n\nOwn full-stack implementation and integrations — build across LLMs, APIs, backend systems, and lightweight UIs to deliver complete, working solutions.\nBuild and own the retrieval layer powering our agents: chunking strategies, hybrid search (vector + keyword), reranking, and grounded citation.\nDesign and optimize embedding pipelines and vector indexes using pgvector and OpenSearch.\nEvaluation, Safety & Reliability\n\nDevelop agentic harnesses to accelerate development — create evaluation frameworks, toolchains, and workflows that enable rapid iteration and improve system reliability.\nOwn the eval stack: curate golden sets, maintain offline regression suites, implement LLM-as-judge, and run online A/B and shadow evals.\nEnsure reliability, safety, and production readiness — implement guardrails, validation logic, and fallback mechanisms to ensure consistent and trustworthy behavior in production.\nTechnology Stack\nLanguages\nPython, Node.js, TypeScript Agent / LLM Frameworks LangGraph, LangChain, Claude Agent SDK, MCP, OpenAI SDK\nModels\nAnthropic Claude, OpenAI, open-weight where appropriate Retrieval & Data PostgreSQL, pgvector, OpenSearch, Kafka, Redshift, Redis\nInfrastructure\nAWS, Kubernetes (EKS), ArgoCD, Terraform Evals & Observability LangSmith / Langfuse / Braintrust, DataDog\n\nQualifications\nEducation & Experience\n\nBachelor's degree in Computer Science, Data Science, AI/ML, or related field, or equivalent practical experience through projects, research, internships, or professional work.\n1–5+ years in software engineering (full-stack or backend), or a strong recent graduate with demonstrable project or internship experience at equivalent depth.\nFamiliarity with LLMs or AI-based systems.\nInternship or research experience in a production AI or data-intensive environment is a strong plus.\nRequired Technical Skills\n\nProficiency in Python; comfortable with NumPy, Pandas, and Scikit-learn.\nHands-on experience with at least one LLM framework: LangGraph, LangChain, Claude Agent SDK, or OpenAI SDK.\nUnderstanding of RAG architecture: embedding models, vector databases, hybrid search, and reranking.\nFamiliarity with prompt engineering best practices and awareness of LLM failure modes (hallucination, injection, drift).\nWorking knowledge of SQL and relational databases (PostgreSQL, MySQL, or similar).\nFamiliarity with Git version control and Agile/Scrum practices.\nPreferred\n\nExperience with agent systems, orchestration frameworks (LangGraph, CrewAI,AutoGen), or AI tooling.\nExposure to MCP (Model Context Protocol) or building typed tool interfaces for LLM agents.\nExperience with eval frameworks (LangSmith, Langfuse, Braintrust) or building LLM-as-judge pipelines.\nFamiliarity with cloud platforms — AWS preferred (Azure, GCP also considered).\nExposure to Kubernetes, Docker, ArgoCD, or Terraform for AI service deployment.\nExposure to data compliance requirements: SOC 2, GDPR, CCPA, HIPAA.\nSoft Skills\n\nStrong analytical mindset with intellectual curiosity about agents, evals, and production AI behavior.\nThis role includes regular interaction with customers to understand workflows, validate solutions, and gather feedback.\nClear written and verbal communication; able to explain LLM behavior and tradeoffs to diverse audiences.\nSelf-motivated, detail-oriented, and comfortable operating in a fast-moving environment.\nGenuine interest in the mission of improving outcomes in senior care through responsible AI.\nCandidates should demonstrate experience building LLM-powered applications, evaluating agent behavior, and working through the full development lifecycle from prototype to production.\nThis job description is intended as a summary of the primary responsibilities and qualifications for this position. It is not intended as an all-inclusive list of duties or qualifications that may be required now or in the future.\n\nVisa Sponsorship: Aline is not able to provide visa sponsorship at this time. Applicants must be authorized to work in the United States without sponsorship.","datePosted":"2026-08-04T18:38:10.635Z","dateModified":"2026-08-04T18:38:10.635Z","hiringOrganization":{"@type":"Organization","name":"Aline","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"6289d87c5c1f9bbef796d3ea"},"url":"https://jobsearcher.com/jobs/6289d87c5c1f9bbef796d3ea"}}