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Langgraph Jobs in Oregon (NOW HIRING)

Smarsh

Senior Software Engineer, Python + AI Platform

OR · On-site +1

$121K - $163K/yr

Familiarity with frameworks like LangGraph or equivalent. * AI-native engineering. Experience working on or alongside AI-native engineering teams, where AI agents are first-class participants in the ...

Redapt

Forward Deployed Engineer, Agentic AI

OR · On-site +1

LangGraph / LangChain / CrewAI (Preferred) * MLOps / LLMOps (Preferred) * MCP (Model Context Protocol) (Preferred) Travel required: * Travel typically 20% or less a year Equal Employment Opportunity:

Nvidia

Developer Relations Manager - Omniverse

OR · On-site +1

NCP, LangGraph) and observability tools for monitoring sophisticated, autonomous systems Track record of influencing sophisticated product decisions through positive relationships while also ...

EM Key Solutions Inc

AI Engineer

OR · On-site +1

Python • Azure OpenAI • OpenAI APIs • LangChain • LangGraph • LlamaIndex • Semantic Kernel • RAG • AI Agents • Machine Learning • FastAPI • Azure AI Studio • Azure DevOps • ...

Nvidia

Senior Solutions Architect, Agentic AI

OR · On-site +1

Validated experience building sophisticated agentic and multi-agent AI systems using orchestration frameworks such as LangGraph, LlamaIndex, CrewAI, LangChain, OpenAI Agents SDK -including tool-using ...

Sonatype

Staff Software Engineer - Agentic First

OR · On-site +1

Hands-on experience designing, running, and scaling multi-agent systems (e.g., Claude Code, Codex, Cursor background agents, custom orchestrators, LangGraph-style graphs) - including MCP tooling ...

Autodesk, Inc.

Principal Full Stack Engineer

Portland, OR · On-site

$139K - $249K/yr

Experience building production-grade AI/ML applications using RAG, LangGraph (or similar agent frameworks), and Model Context Protocol (MCP) integrations * Strong experience and understanding of ...

Zillow

OR · On-site

$204K - $326K/yr

Familiarity with various agentic AI frameworks, such as LangGraph, Agents SDK, AutoGen, and production ML infrastructure * A track record of writing articles, patents, and publishing high-impact ...

Zillow

OR · On-site

$194K - $310K/yr

Familiarity with various agentic AI frameworks, such as LangGraph, Agents SDK, AutoGen, and production ML infrastructure * A track record of writing articles, patents, and publishing high-impact ...

Amerilife Group, LLC

AI Solution Engineer

OR · On-site +1

Practical fluency with at least one agent framework or SDK (Claude Agent SDK, LangGraph, LangChain, Databricks Mosaic AI Agent Framework, Semantic Kernel, or similar) and the ability to reason about ...

Autodesk

Principal Full Stack Engineer

Portland, OR · On-site

$139K - $249K/yr

Experience building production-grade AI/ML applications using RAG, LangGraph (or similar agent frameworks), and Model Context Protocol (MCP) integrations * Strong experience and understanding of ...

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Showing results 21-35

All JobsLanggraph JobsLanggraph Jobs in Oregon

Langgraph information

What is a Langgraph?

Langgraph is a framework designed to build, manage, and orchestrate complex workflows for large language models (LLMs). It allows developers to create directed graphs of language model prompts, tools, and custom logic, making it easier to design multi-step, stateful AI applications. Langgraph is especially useful for building conversational agents, automated workflows, and other applications that require LLMs to interact with data or tools in a structured way.

What are some common challenges faced by Langgraph developers when integrating their workflow with existing AI infrastructure?

Langgraph developers often encounter challenges when integrating their workflow with existing AI infrastructure, such as ensuring compatibility with various large language models and managing data flow across multiple APIs. Coordination with data engineers and machine learning specialists is crucial to align model outputs with business requirements, and adapting to rapidly evolving technologies can require continuous learning. Additionally, optimizing performance and maintaining security standards during integration are key considerations to ensure successful deployment.

What are the key skills and qualifications needed to thrive as a Langgraph engineer, and why are they important?

To thrive as a Langgraph engineer, you need a strong background in software engineering, proficiency in Python, and a solid understanding of AI/ML concepts, usually supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), API integrations, and version control systems such as Git is essential. Effective problem-solving, collaboration, and clear communication are crucial soft skills for working with multidisciplinary teams and resolving complex issues. These capabilities are important because they enable the development, scaling, and maintenance of robust AI-driven applications using the Langgraph platform.

What is the difference between Langgraph vs Data Analyst?

AspectLanggraphData Analyst
Required CredentialsTypically requires knowledge of language processing and graph databasesUsually requires a degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI research labs, data-driven organizationsBusiness, finance, healthcare, and marketing sectors
Industry UsageEmerging role in AI and NLP projectsEstablished role in data interpretation and reporting

While Langgraph focuses on language processing and graph database integration, Data Analysts primarily interpret and visualize data to support business decisions. Both roles require analytical skills, but Langgraph specialists often have a background in AI and NLP, whereas Data Analysts typically hold degrees in statistics or related fields.

What are popular job titles related to Langgraph jobs in Oregon?

For Langgraph jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Langgraph jobs in Oregon look for?

The top searched job categories for Langgraph jobs in Oregon are:

What cities in Oregon are hiring for Langgraph jobs?

Cities in Oregon with the most Langgraph job openings:

Langgraph jobs near you
Infographic showing various Langgraph job openings in Oregon as of August 2026, with employment types broken down into 1% Internship, 87% Full Time, 7% Part Time, and 5% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution.

Senior Software Engineer, Python + AI Platform

Smarsh

OR • On-site, Remote

$121K - $163K/yr

Full-time

Posted 22 days ago

Job description

Who are we?

Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines.  Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.

Smarsh is hiring a senior backend/platform engineer to build and scale agentic AI systems for enterprise use. You will build fast-moving, early-stage Python services that integrate AI capabilities into a production agentic platform. Your scope spans workflow execution, scale, reliability, and platform hardening as we grow.

This is not a generic backend role. The focus is building and designing agentic systems, shipping working software, and solving hard platform problems in a fast-moving AI-native environment. You will join a small, high-velocity cross-functional group and own problems end to end, designing and building from scratch, making fast architectural calls, and driving ideas from whiteboard to working system with a small, high-agency team.

What will you do?
  • Drive backend development for AI workflows as part of a collaborative team. Build and evolve Python/FastAPI services powering core agentic workflows and platform capabilities.
  • Productionize LLM integrations. Implement systems around Bedrock usage, quotas, retries, failover, cost controls, model configuration, and approval constraints.
  • Design for security and compliance. Address customer data handling, tenant isolation, auditability, observability, and secure processing for regulated workloads. Apply auditable data design patterns to ensure AI outputs are traceable, reproducible, and built to withstand regulatory scrutiny.
  • Build for scale. We're a nimble team, but our enterprise customers process data at petabyte scale. Help the platform grow to meet that bar through async job orchestration, performance tuning, and data-layer optimization.
  • Support multi-tenant architecture. Contribute to tenant-aware services, role-based access, SSO integration, and admin/reporting capabilities.
  • Improve platform reliability. Add monitoring, tracing, alerting, and operational tooling for LLM pipelines, workflow execution, and report generation.
  • Build real-time capabilities. Design and implement real-time event delivery and pub/sub patterns to support live workflow state, notifications, and agent feedback loops.
  • Contribute to technical decisions. Partner on shared services decisions, platform architecture, and integration boundaries across the stack.
  • Work across ambiguity. Translate evolving product requirements and non-functional requirements into practical technical solutions with product, architecture, legal, and security stakeholders.
  • Champion code quality. Drive strong typing, automated testing, and continuous integration practices that keep the team fast and safe.
  • Design typed API contracts. Own the API surface as a product contract: designing clean, schema-driven APIs that support typed client generation and reliable integration across services.

What will you bring?
  • Strong Python backend engineering. 7+ years professional software development, including 5+ years building Python services in production. Deep experience with APIs, async processing, background jobs, and workflow orchestration.
  • Cloud-native backend experience. AWS experience, ideally with services relevant to secure enterprise workloads (compute, storage, networking, CI/CD, identity, secrets, encryption).
  • Production distributed systems. Proven ability to productionize complex backend systems with reliability, observability, retries, throughput, failure handling, and performance tuning.
  • Data-intensive system design. Strong knowledge of PostgreSQL, large-scale data processing patterns, indexing, query tuning, and batch/stream tradeoffs. Experience with retrieval-augmented generation (RAG), vector search, and embedding-based systems is required (not a plus).
  • Security and compliance mindset. Experience with multi-tenant systems, RBAC, audit logging, secure data handling, and regulated environments.
  • Strong ambiguity handling. Ability to work from partial requirements and shape implementation around product and non-functional requirement constraints.
  • Agentic workflow engineering. Hands-on experience building LLM-driven workflows: tool-calling, state machines, human-in-the-loop approval patterns, checkpoint/resume, and multi-step agent orchestration. Familiarity with frameworks like LangGraph or equivalent.
  • AI-native engineering. Experience working on or alongside AI-native engineering teams, where AI agents are first-class participants in the development workflow, not just productivity tools. Includes hands-on prompt engineering, eval design, and LLM cost optimization: caching strategies, token efficiency, and model selection tradeoffs.
  • Product mindset. Bias for shipping, learning from real usage, and making pragmatic tradeoffs grounded in customer problems.
Strong Pluses
  • LLM / AI platform experience. Bedrock, OpenAI, Anthropic, LangChain/LangGraph, prompt workflows, evals, tool-calling systems. Experience integrating external AI services safely and reliably.
  • Identity and access. SSO/SAML/OIDC, enterprise auth patterns.
  • Graph-shaped data and entity resolution. Experience with graph-backed data models, entity deduplication, mention linking, and building systems that reason over connected, structured records.
  • Observability stack. OpenTelemetry, tracing, metrics, alerting, cost/usage dashboards.
  • Regulated communications or compliance domain. Background in systems that handle sensitive communications, audit trails, or data subject to legal or regulatory review is a meaningful differentiator.
  • Infrastructure as code. Terraform, feature flags, canary deployments, release strategies.
$195,000 - $260,000 a year
The salary range above represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting. Any applicable bonus programs will be discussed during the recruiting process.
 
The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training.
 
Local cost of living assessments are done for each new hire at the time of offer.
About our culture

Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world's leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.
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