Staff Engineer (Agentic AI)

Kforce Inc; Phoenix (AZ); Vor Ort; USD 180.000 - 240.000; Vollzeit

Benefits dieser Stelle

Medical/Dental/Vision insurance

HSA/FSA

401(k)

Paid time off

Zusammenfassung

Kforce is seeking a Staff Engineer (Agentic AI) in Phoenix, AZ to own end-to-end development of an enterprise Agentic AI platform, enabling autonomous task planning and execution.

You will design and deploy high-performance GenAI capabilities, ensure scalability and security, align with Enterprise Architecture, and drive patterns for prompt, context, and agent management. The role requires deep GenAI expertise and leadership across engineering teams.

Qualifikationen

• 10+ years designing, developing, and deploying enterprise-scale tech solutions.
• 2+ years GenAI/LLM or software architecture initiatives.
• Deep understanding of transformer-based models and GenAI techniques.
• Experience integrating LLMs into enterprise apps with prompt and context engineering.

Aufgaben

• Own end-to-end development of the enterprise's Agentic AI platform.
• Design, develop, test, and deploy high-performance GenAI capabilities.
• Ensure scalable, highly available platforms for mission-critical apps.
• Provide technical direction on GenAI projects across the organization.
• Lead architectures with LLMs, agent frameworks, and AI services.
• Establish reproducible experiments and version control for prompts/agents/datasets.

Kenntnisse

GenAI architecture

LLM integration

Prompt engineering

Agentic AI knowledge

NLP fundamentals

Tools

LangChain

LangGraph

Semantic Kernel

Vector databases

pgvector

Jobbeschreibung

Responsibilities

Kforce has a client that is seeking a Staff Engineer (Agentic AI) in Phoenix, AZ. Duties Include:

• Own the end-to-end development of the enterprise's Agentic AI platform
• Design, develop, test, and deploy high-performance generative AI capabilities that allow AI agents to autonomously understand, plan, and execute multi-step tasks with minimal human oversight
• Ensure the platform is scalable, highly available, and can support mission-critical applications
• Provide technical direction across the organization on GenAI-related projects
• Work closely with Solution and Enterprise Architects to develop solution architectures that integrate LLMs, agent frameworks, and AI services into the broader enterprise system, ensuring alignment with Enterprise Architecture principles and non-functional requirements (security, scalability, resilience, token economics, and latency budgets)
• Lead by example in coding standards, prompt engineering, and context engineering best practices; Conduct code, prompt, and context-pipeline reviews to ensure high code quality, readability, and robust test coverage-including evals, regression suites, and golden datasets for LLM pipelines and API integrations; Establish guidelines for reproducible experiments and version control of prompts, contexts, agents, and datasets (e.g., using Git and LLMOps tools)
• Build internal frameworks and orchestration pipelines to integrate LLMs and agents with enterprise data sources and services; Leverage GenAI tools and protocols (e.g., MCP, A2A, function/tool calling) to enable high-value GenAI business cases across the organization
• Implement LLMOps/GenAI Ops best practices such as automated evaluation, prompt and agent versioning, online/offline evals, observability (traces, token usage, hallucination and grounding metrics), guardrails, and CI/CD pipelines for prompt, agent, and model deployment

Responsibilities

Kforce has a client that is seeking a Staff Engineer (Agentic AI) in Phoenix, AZ. Duties Include:

• Own the end-to-end development of the enterprise's Agentic AI platform
• Design, develop, test, and deploy high-performance generative AI capabilities that allow AI agents to autonomously understand, plan, and execute multi-step tasks with minimal human oversight
• Ensure the platform is scalable, highly available, and can support mission-critical applications
• Provide technical direction across the organization on GenAI-related projects
• Work closely with Solution and Enterprise Architects to develop solution architectures that integrate LLMs, agent frameworks, and AI services into the broader enterprise system, ensuring alignment with Enterprise Architecture principles and non-functional requirements (security, scalability, resilience, token economics, and latency budgets)
• Lead by example in coding standards, prompt engineering, and context engineering best practices; Conduct code, prompt, and context-pipeline reviews to ensure high code quality, readability, and robust test coverage-including evals, regression suites, and golden datasets for LLM pipelines and API integrations; Establish guidelines for reproducible experiments and version control of prompts, contexts, agents, and datasets (e.g., using Git and LLMOps tools)
• Build internal frameworks and orchestration pipelines to integrate LLMs and agents with enterprise data sources and services; Leverage GenAI tools and protocols (e.g., MCP, A2A, function/tool calling) to enable high-value GenAI business cases across the organization
• Implement LLMOps/GenAI Ops best practices such as automated evaluation, prompt and agent versioning, online/offline evals, observability (traces, token usage, hallucination and grounding metrics), guardrails, and CI/CD pipelines for prompt, agent, and model deployment

Requirements

• 10+ years of experience in designing, developing, and deploying enterprise-scale technology solutions, ideally with two years focused on GenAI/LLM or software architecture initiatives; Demonstrated ability to design and manage complex platforms or products at scale
• 7 - 10 years of progressively complex experience building and scaling enterprise software systems-combined with recent, hands-on application of GenAI or Agentic AI technologies in production environments
• Deep understanding of Generative AI techniques and transformer-based models (e.g., Claude, GPT, or other foundation and open-source LLMs); Hands-on experience integrating, and adapting LLMs into enterprise applications, including expertise in prompt engineering, context engineering, retrieval-augmented generation (RAG), GraphRAG, and agentic patterns (ReAct, planner/executor, multi-agent orchestration) for grounding outputs in enterprise data; Familiarity with multi-agent AI systems and agent-based architectures is highly desirable
• Proficiency in modern GenAI frameworks/libraries such as LangChain, LangGraph, Semantic Kernel, or similar tools; Experience with model-serving runtimes and agent orchestration frameworks for building and managing complex GenAI pipelines; Strong grasp of NLP fundamentals, tokenization, embeddings, and knowledge representation; experience with multimodal models, function calling, structured output, and reinforcement learning from feedback (RLHF/RLAIF) is a plus
• Strong background in data engineering and architecture for AI-ready data-skilled in curating, chunking, enriching, and governing unstructured and semi-structured corpora for LLM consumption; Hands-on experience with vector databases (e.g., pgvector, Elastic Search), hybrid search, reranking, knowledge graphs, and embedding strategies for high-quality retrieval

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.

• We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees.
• Salaried personnel receive paid time off.
• Hourly employees are not eligible for paid time off unless required by law.
• Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.

This job is not eligible for bonuses, incentives or commissions.

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.