Senior AI Engineer, Agentic Systems in United States at Jobgether
NewJob Function: Information Technology
Jobgether
United States, United States
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Job Description
Senior AI Engineer, Agentic Systems
Accountabilities:
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior AI Engineer, Agentic Systems in the United States.
This is an exciting opportunity for an experienced AI engineer to lead the design and deployment of advanced agentic systems that solve complex enterprise workflows at scale. In this role, you will work on cutting-edge generative AI solutions, building intelligent multi-agent architectures that integrate tools, data sources, and governance frameworks into secure and production-ready systems. The position offers significant ownership across architecture, orchestration, observability, and AI safety initiatives while collaborating directly with enterprise stakeholders. You will operate in a highly innovative and fast-moving environment where experimentation, measurable outcomes, and engineering excellence are deeply valued. Ideal candidates are passionate about production-grade LLM systems, scalable AI infrastructure, and building reliable AI-powered applications that create meaningful business impact. This role is well suited for someone who enjoys solving technically challenging problems while shaping the future of enterprise AI adoption.
- Design and implement scalable multi-agent architectures with advanced orchestration, memory management, routing, and policy enforcement capabilities.
- Evaluate and deploy leading agentic frameworks such as LangGraph, LangChain Agents, AutoGen, CrewAI, LlamaIndex Agents, Semantic Kernel, or Haystack Agents.
- Build reusable AI system components including planners, evaluators, tool registries, policy guards, and workflow orchestration modules.
- Integrate enterprise tools, APIs, structured data sources, and event-driven systems through function calling, webhooks, and automation pipelines.
- Develop and optimize retrieval-augmented generation (RAG) architectures using vector databases, structured knowledge systems, and advanced grounding strategies.
- Implement reliability mechanisms such as tracing, observability, monitoring dashboards, caching, circuit breakers, and cost optimization frameworks.
- Build evaluation pipelines and testing frameworks to assess task success, groundedness, safety, latency, and operational performance.
- Establish CI/CD pipelines, deployment workflows, feature flag systems, and production release strategies for AI applications.
- Enforce AI safety, governance, privacy, and compliance standards including role-based access control, data minimization, and policy enforcement.
- Collaborate directly with enterprise clients and internal teams to translate business workflows into scalable AI-driven solutions and production deployments.
- Contribute to reusable frameworks, templates, and best practices supporting future enterprise AI initiatives.
- 5–8+ years of experience in software engineering, platform engineering, or AI systems development with recent hands-on experience building production LLM applications.
- Strong expertise with agentic AI frameworks such as LangGraph, LangChain Agents, AutoGen, CrewAI, LlamaIndex Agents, Semantic Kernel, or Haystack Agents.
- Deep experience designing and optimizing RAG pipelines, vector database architectures, chunking strategies, embeddings, and retrieval systems.
- Proven track record building secure, observable, scalable, and cost-efficient AI systems in production environments.
- Strong programming skills in Python and/or TypeScript with experience in APIs, asynchronous programming, testing, CI/CD, and containerized environments.
- Hands-on experience with tracing, evaluation frameworks, guardrails, identity and access management, secrets handling, and PII protection.
- Strong understanding of AI safety, governance, compliance, and enterprise security standards such as ISO 27001, SOC 2, HIPAA, or GDPR.
- Excellent communication skills with the ability to collaborate with technical teams, business stakeholders, and enterprise clients.
- Experience with Azure AI services, Azure OpenAI, Azure Functions, AKS, or cloud-native AI infrastructure is highly valued.
- Additional experience with AWS, GCP, hybrid cloud environments, enterprise integrations, structured outputs, or constrained decoding methodologies is a plus.
- Competitive salary or contract compensation based on experience and engagement model.
- Fully remote and flexible work environment within the United States.
- Opportunity to work on impactful, production-grade enterprise AI systems.
- Collaborative and innovation-focused engineering culture.
- Access to continuous learning opportunities, technical deep dives, certifications, and knowledge-sharing sessions.
- High level of ownership and autonomy within a fast-moving team environment.
- Inclusive workplace culture that supports flexibility, creativity, and professional growth.
- Exposure to cutting-edge technologies in generative AI, orchestration systems, and enterprise automation.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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Job Location
United States, United States
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