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Agentic Developers Jobs in Reno, NV (NOW HIRING)

Equs, Inc.

Senior AI Engineer

Reno, NV · Remote

$107K - $146K/yr

Design the context augmentation pipelines, spanning vector RAG, CAG, agentic file exploration, Text-to-SQL, knowledge graphs, fine-tuning, and MCP-based context engineering, and select the right ...

New

Teradata Corporation (SE)

Staff AI Engineer

Carson City, NV · On-site

$169.40 - $254.10/hr

Own end-to-end architecture for critical AI capabilities such as agentic workflows, RAG pipelines ... Establish engineering standards that improve development velocity, quality, and operational ...

Socure

Head of Sales

Carson City, NV · On-site

$350 - $600/hr

... value engineering, and C‑suite engagement across key verticals. * Scale partner and channel ... Embed AI and automation into the commercial engine , using tools and agentic workflows to improve ...

Socure

Head of Sales (Carson City)

Carson City, NV · On-site

... value engineering, and C‑suite engagement across key verticals. * Scale partner and channel ... Embed AI and automation into the commercial engine , using tools and agentic workflows to improve ...

All JobsAgentic Developers JobsAgentic Developers Jobs in Reno, NV

Agentic Developers information

See Reno, NV salary details

$34.9K

$70.8K

$229.8K

How much do agentic developers jobs pay per year?

As of Aug 28, 2026, the average yearly pay for agentic developers in Reno, NV is $70,808.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,900.00 and $59,800.00 per year, depending on experience, location, and employer.

What is an agentic developer?

Agentic developers are software professionals who design, build, or work with systems that exhibit agency—meaning the system can make autonomous decisions and take actions to achieve specific goals. These developers often focus on creating advanced AI agents, multi-agent systems, or applications that integrate autonomous behaviors. Their work typically involves a mix of programming, machine learning, and system design to enable intelligent, proactive software. Agentic developers are increasingly in demand as AI-driven applications become more common across industries.

How do agentic developers typically collaborate with cross-functional teams to implement autonomous systems?

Agentic Developers often work closely with data scientists, UX/UI designers, and product managers to build and integrate autonomous agents within larger software systems. Collaboration usually involves regular sprint meetings, sharing progress on task automation, and aligning system behaviors with user and business requirements. This multidisciplinary teamwork ensures that agentic solutions are robust, user-friendly, and aligned with organizational goals. Open communication and a willingness to iterate on feedback are key to success in this role.

What are the key skills and qualifications needed to thrive as an agentic developer, and why are they important?

To thrive as an Agentic Developer, you need a solid background in software engineering, AI/ML concepts, and agent-based systems, often supported by a degree in computer science or related fields. Familiarity with frameworks such as LangChain, OpenAI APIs, and experience with cloud platforms and workflow orchestration tools are typically expected. Strong problem-solving, critical thinking, and effective communication skills set top performers apart in this emerging field. These competencies enable Agentic Developers to design, build, and manage intelligent, autonomous agents that deliver innovative solutions and adapt to complex real-world tasks.

What is the difference between Agentic Developers vs Software Engineers?

AspectAgentic DevelopersSoftware Engineers
Required CredentialsBachelor's in Computer Science or related field, coding certificationsBachelor's in Computer Science or related field, coding certifications
Work EnvironmentCollaborative teams, project-based settings, tech companiesDevelopment teams, tech firms, startups, corporate IT departments
Employer & Industry UsageTech startups, software firms, digital agenciesTech companies, software development firms, enterprise IT
Search & Comparison IntentYesYes

Agentic Developers and Software Engineers share similar credentials and work environments, often overlapping in tech companies and startups. However, Agentic Developers typically emphasize a proactive, autonomous approach to project execution, whereas Software Engineers focus more on designing, coding, and maintaining software solutions. Understanding these distinctions helps employers and job seekers align expectations and roles effectively.

Is agentic developer a good career?

Agentic developer is not a standard job title; if referring to a developer with agency or autonomy in their work, software development is generally considered a good career due to high demand, competitive salaries, and opportunities for remote work. Success often depends on technical skills, problem-solving ability, and continuous learning in programming languages and tools.

What are popular job titles related to Agentic Developers jobs in Reno, NV?

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The top searched job categories for Agentic Developers jobs in Reno, NV are:

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Cities near Reno, NV with the most Agentic Developers job openings:

Agentic Developers jobs near you

Senior AI Engineer

Reno, NV • Remote

Equs, Inc.
See more jobs at Equs, Inc.external

$107K - $146K/yr

Full-time

Posted 2 days ago

New

Job description

OUR VISIONEQUS is building the trust infrastructure for personal AI. Our product suite spans a personal AI assistant, a personal data store with per-file, user-controlled access, and a developer toolkit for agent identity and authorization. It all runs on a single permission rail designed around one principle: your data belongs to you. We are preparing for a major public launch and scaling from build mode to operate-at-scale mode.WHAT YOU WILL DOAs a Senior AI Engineer at EQUS, you own the AI assistant layer end to end: architecture, standards, and the service contracts that security, storage and front-end engineers support. You are a technical decision-maker, not only an implementer. You recommend the right approach for each problem, and you are prepared to say "this does not need AI" when it doesn’t. Privacy, safety, and cost sit at the center of every call you make. Your day-to-day includes, but is not limited to:
  • AI architecture and context engineering. Design the context augmentation pipelines, spanning vector RAG, CAG, agentic file exploration, Text-to-SQL, knowledge graphs, fine-tuning, and MCP-based context engineering, and select the right approach for each use case.  Select chunking strategy, embedding models, and retrieval architecture for user-owned document systems with multi-tenant isolation.  Privacy and security guides each decision.
  • LLM integration and agent systems. Integrate and manage commercial and open-source LLM APIs, and deploy multi-agent systems with LangChain, LlamaIndex, or LangGraph. Lead model selection, prompt engineering, fine-tuning, and production evaluation across the AI stack.
  • Evaluation and optimization. Build evaluation frameworks that measure output quality, relevance, and safety. Optimize pipelines for latency, token cost, and throughput, monitor production for drift and regression, and close the feedback loop from evals back into iteration.
  • Privacy and safety engineering. Privacy is our product, not a compliance checkbox. Own PII handling, GDPR and CCPA compliance, encryption at rest and in transit, and user-scoped access boundaries at the systems level. Build prompt injection defenses, output filtering, and data leakage prevention, and partner with security and trust experts on agentic workflow guardrails and shadow AI detection.
  • Infrastructure and standards. Deploy and operate production AI systems on AWS, Docker and Kubernetes, and GitLab. Define the AI service contracts and APIs other engineers build on top of, and set the standard for how AI works here, including mentoring engineers and raising the technical bar around you.
WHAT YOU WILL NEED TO SUCCEEDYou have shipped AI in production, you know where pipelines break, and you make architectural decisions that prove right. You exercise strong judgment on build vs. buy and on what separates an MVP from a production system, and you know the cost-performance tradeoffs cold: when a smaller fine-tuned model outperforms a general-purpose large one, and when expanding the context window beats RAG.
You treat AI safety as a first-class engineering concern rather than a review-stage checklist.  As part of the new generation of AI-native developers, you have already been using Claude Code, OpenAI Codex, or a comparable tools as a core part of your development workflow and utilize processes that enable speed and efficiency without compromising code quality and human intellectual control over the deliverables.
You have experience in both small and large teams, effectively use tools such as Jira and Confluence, and are a valuable colleague to product managers as new features and products are emerging.  You have experience working effectively with consultants and outsourced development teams, including transitioning responsibilities for systems.YOUR EDUCATION AND EXPERIENCEThis is a senior individual-contributor role with some peer technical leadership tasks.  A relevant degree in computer science or engineering is preferred but highly qualified individuals with demonstrated experience shipping AI products at scale are welcome. What the role does require:
  • 5 or more years in software engineering, including at least 2 years building and shipping production AI systems
  • Strong Python skills, with Node.js or .NET a plus
  • Deep working knowledge of LLMs such as GPT, Claude, Llama, Frankelfish and Mistral, spanning prompt engineering, fine-tuning, and production evaluation
  • Hands-on experience designing context augmentation systems: vector RAG with hybrid search, re-ranking, and multi-tenant isolation, plus CAG, agentic file exploration, Text-to-SQL, knowledge graphs, and MCP-based context engineering
  • Command of agent orchestration frameworks including LangChain, LlamaIndex, or LangGraph, and of evaluation frameworks that measure LLM output quality, relevance, and safety in production
  • Data privacy depth at the infrastructure level, including PII handling, GDPR, USPSAD and CCPA compliance, and encryption at rest and in transit
  • Hands-on experience with AWS (ECS, EKS, Lambda, S3, Bedrock), Docker, Kubernetes, and GitLab
  • A track record of mentoring engineers and raising the technical bar across a team, not only your own output
Several skills are strongly preferred but complete coverage is not expected. Experience running local open-source models such as Llama, Mistral, or Mixtral via Ollama, vLLM, or llama.cpp is a significant plus, as is fine-tuning with LoRA or QLoRA. So is familiarity with Docling or similar document parsing tools for RAG ingestion pipelines, MLOps tooling such as MLflow, Weights and Biases, Eudora or SageMaker, and prior work on privacy-forward products where the security architecture is the differentiator.
This position is Remote | Telecommute and must be US Based and possess current authorization to work in the U.S. without sponsorship.

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