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Ai Officer Jobs (NOW HIRING)

Worth AI

Senior Agentic (AI) Engineer

Miami, FL · On-site +1

$99K - $137K/yr

You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment and partner closely with our Chief AI Officer, applied scientists, and platform teams. Responsibilities

Worth AI

Senior Agentic (AI) Engineer

Orlando, FL · On-site +1

$97K - $134K/yr

You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment and partner closely with our Chief AI Officer, applied scientists, and platform teams. Responsibilities

Worth AI

Senior Agentic (AI) Engineer

Miami, FL · Remote

$107K - $146K/yr

You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment and partner closely with our Chief AI Officer, applied scientists, and platform teams. Responsibilities

Worth AI

Senior Agentic (AI) Engineer

Orlando, FL · On-site +1

$97K - $134K/yr

You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment and partner closely with our Chief AI Officer, applied scientists, and platform teams. Responsibilities

Worth AI

Senior Agentic (AI) Engineer

Atlanta, GA · On-site +1

$100K - $138K/yr

You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment and partner closely with our Chief AI Officer, applied scientists, and platform teams. Responsibilities

Worth AI

Senior Agentic (AI) Engineer

Tampa, FL · On-site +1

$98K - $135K/yr

You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment and partner closely with our Chief AI Officer, applied scientists, and platform teams. Responsibilities

Worth AI

Senior Agentic (AI) Engineer

Atlanta, GA · Remote

$107K - $146K/yr

You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment and partner closely with our Chief AI Officer, applied scientists, and platform teams. Responsibilities

Worth AI

Senior Agentic (AI) Engineer

Tampa, FL · Remote

$107K - $146K/yr

You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment and partner closely with our Chief AI Officer, applied scientists, and platform teams. Responsibilities

Cornerstone Defense

Data & AI Champion

Bethesda, MD · On-site

Data & AI Champion- Seeking a proactive and detail-oriented Program Support Team Member to support the Chief AI Officer and Chief Data Officer (CAIO/CDO) of one of our Intelligence customers. This ...

Arcade AI, Inc

Enterprise Account Executive

New York, NY · On-site

$200K/yr

Our buyers are Heads of AI, Chief AI Officers, CTOs, CIOs, and CISOs at companies that have moved past chatbots and need their AI to actually take secure actions across Google, Slack, Salesforce, and ...

Genpact LLC

Chief AI Engineer

Port Reading, NJ · On-site

$165.30 - $235/hr

Be the trusted technical advisor to client executives (CIO, CDO, Chief AI Officer, CFO). Strategy in the morning, working demo in the afternoon.Architect and build the hardest parts of the hardest ...

New

Blackbaud

Enterprise Architect

$70.75 - $91/hr

... AI Officer to establish responsible AI guardrails, including governance, security, privacy, explainability, and regulatory compliance • Collaborate with Chief Data & AI Officer, Security and Legal ...

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Ai Officer information

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$23.5K

$75.9K

$182.5K

How much do ai officer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for ai officer in the United States is $75,929.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,000.00 and $98,500.00 per year, depending on experience, location, and employer.

What is an AI officer?

AI Officers are professionals responsible for overseeing the development, implementation, and ethical management of artificial intelligence technologies within an organization. They guide AI strategy, ensure compliance with regulations, and collaborate with different departments to integrate AI solutions effectively. Their role often includes evaluating AI risks, promoting responsible AI use, and aligning AI initiatives with business goals. AI Officers typically have a background in technology, data science, and policy, making them key players in leveraging AI for organizational success.

What skills and qualifications are needed to thrive as an AI officer?

To thrive as an AI Officer, you need a solid understanding of artificial intelligence, data analysis, and machine learning, typically supported by a degree in computer science, engineering, or a related field. Familiarity with AI frameworks (like TensorFlow or PyTorch), programming languages (such as Python), and relevant certifications (e.g., AI or data science certifications) is highly valued. Strong problem-solving, communication, and project management skills set exceptional candidates apart in this role. These competencies are crucial for effectively developing, implementing, and overseeing AI strategies that align with organizational goals.

How does an AI officer typically collaborate with cross-functional teams within an organization?

AI Officers often work closely with cross-functional teams such as data scientists, IT specialists, product managers, and business leaders to identify opportunities for AI implementation. They play a key role in translating business objectives into technical AI solutions and ensuring that projects align with organizational goals. Regular communication and collaboration are essential, as AI Officers must bridge the gap between technical and non-technical stakeholders to drive successful AI initiatives.

What is the difference between Ai Officer vs Data Analyst?

AspectAi OfficerData Analyst
Required CredentialsDegree in AI, Computer Science, or related field; certifications in AI/MLDegree in Data Science, Statistics, or related field; certifications in data analysis
Work EnvironmentTech companies, R&D labs, AI-focused departmentsBusiness, finance, marketing, and healthcare sectors
Employer & Industry UsageOrganizations developing AI solutions, tech firmsOrganizations analyzing data to inform decisions across industries

The main difference is that an Ai Officer focuses on developing and implementing AI technologies, while a Data Analyst interprets data to support business decisions. Both roles require analytical skills, but Ai Officers typically have specialized knowledge in AI/ML algorithms and programming, working more on the technical development side. Data Analysts often focus on data visualization and reporting to help organizations understand trends and insights.

How to become an AI officer?

To become an AI officer, candidates typically need a bachelor's degree in computer science, data science, or a related field, with many roles requiring a master's or Ph.D. in artificial intelligence, machine learning, or similar areas. Developing skills in programming languages like Python, experience with AI frameworks, and knowledge of data analysis are essential. Relevant certifications and hands-on experience with AI projects can also improve job prospects.

What does an AI officer do?

An AI officer is responsible for developing, implementing, and managing artificial intelligence strategies within an organization. They often work with machine learning models, data analysis, and AI tools to improve business processes and decision-making. Strong technical skills, knowledge of AI frameworks, and understanding of ethical considerations are essential for this role.
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Ai Officer jobs near you
Infographic showing various Ai Officer job openings in the United States as of August 2026, with employment types broken down into 96% Full Time, and 4% Part Time. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $75,929 per year, or $36.5 per hour.

Senior Agentic (AI) Engineer

Worth AI

Miami, FL • On-site, Remote

$99K - $137K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago

Job description

Worth AI is hiring a Senior Agentic AI Engineer to design and ship production agent systems that automate KYB, underwriting, and risk decisions on regulated financial data. You'll own agents end-to-end architecture, retrieval, tools, evals, and production deployment and partner closely with our Chief AI Officer, applied scientists, and platform teams.

Responsibilities
  • Design and ship multi-step agentic systems (planner/executor, tool-using, multi-agent, human-in-the-loop) for onboarding, underwriting, case review, and continuous monitoring.
  • Architect agent graphs in LangGraph (or comparable - CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks.
  • Build the retrieval layer powering our agents - chunking, hybrid search, reranking, and grounded citation.
  • Own the eval stack: golden sets, offline regression suites, LLM-as-judge, online A/B and shadow evals, and red-teaming for jailbreaks, prompt injection, and PII leakage.
  • Expose agents to production systems via well-typed tools and MCP servers. Treat tool surface area as a product.
  • Drive production MLOps: deployment, versioning, traffic shaping, cost/latency budgets, tracing, and on-call playbooks for agent incidents.
  • Partner with security and compliance to keep agents inside SOC 2, GDPR, CCPA, and fair-lending posture - auditability and explainability built in, not bolted on.
  • Mentor engineers on agent patterns, prompt hygiene, eval discipline, and LLM failure modes.
  • Technology Stack
    • Languages: Python, Node.js, TypeScript
    • Agent / LLM frameworks: LangGraph, LangChain, Claude Agent SDK, MCP, OpenAI SDK
    • Models: Anthropic Claude, OpenAI, open-weight where appropriate
    • Retrieval & Data: PostgreSQL, pgvector, OpenSearch, Kafka, Redshift, Redis
    • Infra: AWS, Kubernetes (EKS), ArgoCD, Terraform
    • Evals & Observability: LangSmith / Langfuse / Braintrust-style tooling, DataDog

Requirements

  • 5+ years of software engineering experience, with 2+ years building production LLM or agentic systems (not just notebooks or demos).
  • Hands-on experience with a modern agent framework (LangGraph strongly preferred) and a track record of shipping agents that run, fail gracefully, and recover.
  • Strong RAG fundamentals chunking, embeddings, hybrid retrieval, reranking, grounding - and judgment about when RAG isn't the right answer.
  • Real eval experience golden sets, offline and online evaluations, used to make ship/no-ship calls.
  • Production MLOps fluency: deployed LLM workloads under real latency, cost, and reliability constraints.
  • Strong Python; comfortable in TypeScript / Node.js.
  • Solid systems engineering instincts APIs, async patterns, queues, databases, distributed system failure modes.
  • Calibrated communicator; thrives in ambiguous, fast-moving environments.
  • Prior experience in fintech, lending, payments, KYB/KYC, fraud, or AML.
  • Experience building MCP servers or other structured tool interfaces for LLMs.
  • Background in classical ML (ranking, scoring, calibration).
  • Experience designing explainable / auditable AI workflows for regulated environments.
  • Open-source contributions to agent frameworks, eval tooling, or retrieval libraries.
  • AWS depth (EKS, MSK, RDS, S3, Lambda) and IaC with Terraform.
Success Metrics
  • Agent Quality: Measurable improvements in task success rate, grounding accuracy, and hallucination rate on our eval suites.
  • Production Reliability: Agents you own meet defined SLOs for latency (P90/P99), tool-call success, and cost per task.
  • Velocity: New agent capabilities go from prototype to production in weeks, without skipping evals or guardrails.
  • Risk Posture: Zero material incidents tied to prompt injection, PII leakage, or unsafe tool use on agents you own.
  • Force Multiplier: Patterns, tools, and eval scaffolding you build get adopted across engineering.

All Remote Hires will be required to travel to Orlando, Florida at least twice per year for Town Halls and team collaboration, in addition to orientation in Orlando.

Benefits

  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k, IRA)
  • Life Insurance
  • Flexible Paid Time Off
  • 9 paid Holidays
  • Family Leave
  • Remote
  • Hybrid work (for Orlando Associates)
  • Free Food & Snacks (Orlando)
  • Wellness Resources

Apply