Jobs

What you will do

In this role you will build the agentic systems that power Teradata's next generation of AI-driven analytics - intelligent agents that reason over enterprise data, invoke Vantage capabilities as tools, and complete multi-step analytical tasks autonomously.

You will design and implement agent skills and plugins that extend the Teradata agent harness, build evaluation frameworks to measure agent quality, and contribute to the reliability and performance of agent workflows running on Vantage. Your work directly enables customers to move from asking Teradata questions to delegating analytical tasks to AI agents.

Success looks like agents in production that solve real customer problems - with measurable accuracy, latency, and reliability benchmarks that outperform what is possible on Snowflake Cortex or Databricks Genie.

Who you will work with

You will join a focused team of AI engineers within Teradata's AI Apps, Analytics, and UX Engineering organization, working on the most technically ambitious part of the Teradata product roadmap. We ship code, not demos.

This role reports to the Senior Manager of AI Engineering and collaborates closely with Staff AI Engineers, the Agent Platform team, and Product Management. You will have access to Teradata's world-class data infrastructure and the opportunity to shape how enterprise agents work at scale.

What makes you a qualified candidate
3-6 years of software engineering experience with at least 2 years building agentic AI systems in production - not just RAG pipelines or chatbots. Hands-on experience implementing agent skills, plugins, or tools that extend an agent harness (Claude Code, OpenCode, Codex, OpenClaw, LangGraph, or equivalent). Proficiency in Python; Go experience is a strong advantage. Understanding of agent planning loops, tool-calling protocols, function calling APIs (OpenAI, Anthropic, or Google format), and prompt engineering for reliability.
What you will bring
Op

Our Company

At Teradata, we believe that people thrive when empowered with trusted information. Our technology disrupts current thinking and delivers innovative and trusted solutions for the world's toughest data and analytics challenges—all powered by people like you.

What You Will Do

In this role you will build the agentic systems that power Teradata's next generation of AI-driven analytics — intelligent agents that reason over enterprise data, invoke Vantage capabilities as tools, and complete multi-step analytical tasks autonomously.

You will design and implement agent skills and plugins that extend the Teradata agent harness, build evaluation frameworks to measure agent quality, and contribute to the reliability and performance of agent workflows running on Vantage. Your work directly enables customers to move from asking Teradata questions to delegating analytical tasks to AI agents.

Success looks like agents in production that solve real customer problems — with measurable accuracy, latency, and reliability benchmarks that outperform what is possible on Snowflake Cortex or Databricks Genie.

Who You Will Work With

You will join a focused team of AI engineers within Teradata's AI Apps, Analytics, and UX Engineering organization, working on the most technically ambitious part of the Teradata product roadmap. We ship code, not demos.

This role reports to the Senior Manager of AI Engineering and collaborates closely with Staff AI Engineers, the Agent Platform team, and Product Management. You will have access to Teradata's world-class data infrastructure and the opportunity to shape how enterprise agents work at scale.

What Makes You a Qualified Candidate

3–6 years of software engineering experience with at least 2 years building agentic AI systems in production — not just RAG pipelines or chatbots. Hands-on experience implementing agent skills, plugins, or tools that extend an agent harness (Claude Code, OpenCode, Codex, OpenClaw, LangGraph,

Sr. AI Engineer – Agent Orchestration

A high-growth technology company building AI-powered software for US government customers is hiring a Senior AI Engineer focused on agent workflow orchestration. The company’s AI agent has seen rapid adoption, and the team is now pushing it to handle increasingly complex, multi-step tasks either fully autonomously or in a human-in-the-loop mode.

This role is squarely backend and systems-focused. You’ll be designing how an AI agent plans, sequences, and executes long-running workflows — coordinating across multiple tools, data sources, and sub-agents to complete jobs that today require hours of manual work. Think of it as building the brain and nervous system of the agent, not the hands.

What You’ll Do

Architect and build the workflow engine that powers multi-step agent task execution — including planning, sequencing, branching, error recovery, and human handoff pointsDesign and implement multi-agent coordination patterns: routing between specialized sub-agents, managing shared memory and context, and orchestrating parallel workstreamsBuild scalable tool-use infrastructure that lets agents dynamically discover, select, and chain tools based on task requirementsOwn reliability and observability for long-horizon agent tasks — designing checkpointing, retry strategies, and evaluation harnesses that catch failures before users doDefine and enforce the technical architecture and engineering standards for agentic systems across the platform

What We’re Looking For

You have built an LLM reliably completing complex, multi-step tasks in production — not just single-turn Q&A, but real workflows with branching logic, tool calls, and failure handlingDeep experience with workflow orchestration patterns (DAGs, state machines, event-driven architectures) applied to LLM-powered systemsHands-on experience with agent frameworks (Claude Agent SDK, OpenAI Agent SDK, LangGraph, or similar)Strong understanding of LLM reliability e

Company Description

Govini transforms Defense Acquisition from an outdated manual process to a software-driven strategic advantage for the United States. Our flagship product, Ark, supports Supply Chain, Science and Technology, Production, Sustainment, Logistics, and Modernization teams with AI-enabled Applications and best-in-class data to more rapidly imagine, develop, and field the capabilities we need. Today, the national security community and every branch of the military rely on Govini to enable faster and more informed Acquisition decisions.

Job Description

We are seeking an experienced Lead AI Engineer to lead our Agentic AI team as we scale our agentic offerings across all levels of the US government. Over the past year, we have seen the rapid adoption of our agent, Ace. We expect Ace to be handling much more complex tasks and workflows end-to-end and/or in cooperation with a human user as time goes on. The team is striving to make Ace an even more effective agent, focusing on planning, reliable execution over longer time horizon tasks, scaled tool use, Ace Skills, memory, and inter-agent coordination.

In order to do this job well, we are looking for someone who can demonstrate a project built on LLMs that showcases your skill at getting them to do complex tasks.

Experience leading agentic system development from ideation through production, including technical design, architecture decisions, and day-to-day leadership of Data Scientists and Machine Learning Engineers
Experience integrating and working with LLMs, with a strong understanding of their capabilities and limitations
Experience integrating and working with agent frameworks like Claude Agent SDK or OpenAI Agent SDK
Experience building observability, evaluation, and feedback loops for agent behavior (telemetry, prompt evaluation, regression testing, and reliability metrics).
Experience working in highly ambiguous environments, and operating with

This role is part of the Jobright Direct Hiring Network, where top companies like Cresta AI, Plaud, Mercor, OpenArt, and 1,500+ others hire top talent directly through our platform.

This is not a mass job posting. Only select, high-signal candidates are invited and recommended directly to hiring teams

Hiring Company: Creao AI

One-liner: CREAO is redefining the relationship between people and software by empowering users to create custom, conversational AI applications using natural language.

Salary:

Why Join Us:

Role Responsibilities

• Design, develop, and deploy AI agents using LLMs (e.g., GPT, Claude, open-source models)

• Build multi-step reasoning, planning, and tool-using agent workflows

• Integrate AI agents with internal systems, APIs, databases, and third-party services

• Implement evaluation frameworks to measure agent performance, reliability, and safety

• Optimize prompts, memory systems, retrieval pipelines, and agent architectures

• Collaborate with product, engineering, and design teams to translate real-world problems into AI-driven solutions

• Improve system scalability, latency, and cost efficiency

• Monitor agent behavior in production and continuously iterate based on feedback and data

• Ensure responsible AI practices, including privacy, safety, and bias mitigation

Qualitications

Required

• Strong software engineering skills in Python, TypeScript, or similar

• Experience working with LLMs, AI frameworks, or ML systems

• Understanding of agent architectures, such as: Tool use / function calling, Planning & reasoning, Memory & retrieval (RAG)

• Experience integrating APIs, databases, and distributed systems

• Ability to ship production-ready systems with reliability and observability in mind

Preferred

• Experience with frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or similar

• Experience with vector databases (Pinecone, FAISS, Milvus, etc.)

• Knowledge of evaluation methods for generative AI systems

• Experie

About Lyzr

Lyzr is a Series A–backed enterprise AI company building a full-stack agent infrastructure platform that helps organizations design, deploy, and govern AI agents. Our platform enables enterprises to move beyond isolated AI use cases and into reliable, production-grade agentic workflows with strong controls around security, accuracy, and compliance.

Recognized by Accenture and Harvard Business School–led innovation ecosystems, Lyzr works with global enterprises to reimagine complex workflows using agentic AI. We focus on making AI agents dependable at scale - so teams can replace fragmented tool stacks with a unified, governed intelligence layer.

About The Job

You won't just be building interfaces; you will be architecting the future of work. You’ll be at the forefront of the "Third Way" of enterprise AI—combining open-source flexibility with enterprise-grade security. You will build Agentic apps on Lyzr, solving complex client requirements by turning fragmented processes into autonomous, intelligent workflows.

What You’ll Do

Build & Orchestrate: Design and deploy sophisticated AI Agents using the Lyzr Agent Studio and SDKs.

Full-Stack Ownership: Develop end-to-end applications with a heavy focus on Python backends and React frontends.

Client Success: Work closely with enterprise clients to translate business requirements into high-performing agentic architectures.

AI Innovation: Implement multi-agent collaboration, memory systems, and RAG-driven orchestrations.

What You Bring

Experience: 4+ years of professional full-stack development.

Tech Stack: Deep proficiency in Python (FastAPI/Django) and React.js.

AI-Native Workflow: You don’t just use a terminal; you leverage Cursor, Claude Code, and other LLM-powered coding tools to ship 10x faster.

LLM Fluency: Familiarity with LLM orchestration, prompt engineering, and the agentic AI landscape.

Location: Based in or willing to work in New York (This is an immediate, onsite/hybrid position).

Why

Role: AI Agent Developer / Agentic AI Developer

Local to MN candidates (Onsite )

Role Summary

Design, build, and scale autonomous AI agents that augment software engineering, DevSecOps, and enterprise developer workflows using modern large language models (LLMs) and agentic architectures.

Key Responsibilities

Design and develop autonomous and semi autonomous AI agents leveraging LLMs and agentic frameworks to solve complex engineering and operational problems.

Build AI-powered developer productivity tools, including assistants for code generation, review, refactoring, and documentation.

Develop and deploy agents that automate coding, testing, CI/CD, DevSecOps, and quality assurance workflows.

Integrate leading LLM platforms and copilots (e.g., GitHub Copilot, Claude, Codex) into enterprise developer toolchains and workflows.

Architect agent orchestration, tool calling, memory, and feedback loops to ensure reliability, security, and scalability.

Partner with platform, security, and engineering teams to ensure secure, compliant, and production ready AI solutions.

Continuously evaluate emerging LLMs, frameworks, and agentic patterns to drive innovation and best practices.

GAP INTERNATIONAL – A unique, purpose-driven, consulting company

ABOUT GAP INTERNATIONAL

Gap International is a global consulting firm that partners with executives to achieve breakthrough business results. We're a team of passionate problem-solvers committed to innovation and transformation. As part of our growth strategy, we're expanding our AI capabilities to deliver cutting-edge solutions across the enterprise. This role offers the opportunity to work on impactful projects, including dialog-driven learning and business process acceleration.

ABOUT THE ROLE

You will be part of a tight knit, highly collaborative research and development team focused on building real-world AI applications. As an AI/LLM Engineer, you will lead the design and implementation of advanced systems centered on large language models and natural language understanding. Your work will involve techniques such as fine-tuning, retrieval-augmented generation (RAG), and prompt engineering to solve meaningful business challenges.

You will work closely with teams to explore data, shape requirements, and integrate AI capabilities into internal tools and digital products. Your contributions will drive innovation and shape transformative projects across the organization.

RESPONSIBILITIES

Design and implement AI systems using Large Language Models (LLMs) to solve enterprise challenges and improve operational efficiency.
Fine-tune foundation models and apply techniques such as retrieval-augmented generation (RAG) and prompt engineering.
Collaborate with cross-functional teams to integrate AI capabilities into internal tools, workflows, and digital products.
Evaluate and experiment with frameworks and tools like Hugging Face, LangChain, OpenAI, Claude, and LLaMA.
Build and deploy scalable LLM solutions across cloud-based and local environments, leveraging container orchestration tools where applicable.
Lead architectural decisions and guide implementation o

At Lawyer.com, we are revolutionizing how people connect with leading legal professionals. We are looking for an exceptional builder to join our team in a fast-paced environment.

But we are not looking for a traditional engineer who stares at a blank screen and writes code by hand. We are hiring a Model Jockey.

Your job is to build and deploy AI-powered applications, voice solutions, and text agents that drive real business value. You will act as an orchestrator, steering multiple AI instances in parallel to write code, review architecture, and automate complex workflows. You will direct the models, shape their output, catch their mistakes, and ship products faster than a traditional engineering team ever could.

Requirements

Core
• 3 years of Model Jockey experience. (Read here for a definition of a Model Jockey: https://medium.com/@rybeswick/heads-up-knowledge-workers-your-last-job-is-model-jockey-974edf9c1b60)
• Bachelor's degree in Computer Science, AI, or a related field.
• Systems-Level Engineering Instincts: We do not care what specific languages or frameworks you have memorized. We care that you understand underlying architecture, logic, and data flow. You will not be fixing code by hand. Instead, you need the engineering instincts to spot when a model is taking the wrong approach and the ability to rapidly direct the AI to debug and correct its own work in any stack.
• Technology-Agnostic Mindset: You are wired to figure things out. If a project requires a new database, API, or cloud environment, you do not spend weeks reading documentation. You spin up an agent, give it the context, and start building immediately.
• Parallel Orchestration: Proven ability to run multiple AI agents (like Claude Code, OpenAI, GitHub Copilot) simultaneously without losing the thread.
• Strategic Inquiry and Prompting: Knowing how to ask the right questions to pull the best work out of models, creating effective workflows for complex tasks, and optimizing for accuracy.
• Hum

About Lyzr

Lyzr is a Series A–backed enterprise AI company building a full-stack agent infrastructure platform that helps organizations design, deploy, and govern AI agents. Our platform enables enterprises to move beyond isolated AI use cases and into reliable, production-grade agentic workflows with strong controls around security, accuracy, and compliance.

Recognized by Accenture and Harvard Business School–led innovation ecosystems, Lyzr works with global enterprises to reimagine complex workflows using agentic AI. We focus on making AI agents dependable at scale - so teams can replace fragmented tool stacks with a unified, governed intelligence layer.

About The Job

You won't just be building interfaces; you will be architecting the future of work. You’ll be at the forefront of the "Third Way" of enterprise AI—combining open-source flexibility with enterprise-grade security. You will build Agentic apps on Lyzr, solving complex client requirements by turning fragmented processes into autonomous, intelligent workflows.

What You’ll Do

Build & Orchestrate: Design and deploy sophisticated AI Agents using the Lyzr Agent Studio and SDKs.
Full-Stack Ownership: Develop end-to-end applications with a heavy focus on Python backends and React frontends.
Client Success: Work closely with enterprise clients to translate business requirements into high-performing agentic architectures.
AI Innovation: Implement multi-agent collaboration, memory systems, and RAG-driven orchestrations.

What You Bring

Experience: 4+ years of professional full-stack development.
Tech Stack: Deep proficiency in Python (FastAPI/Django) and React.js.
AI-Native Workflow: You don’t just use a terminal; you leverage Cursor, Claude Code, and other LLM-powered coding tools to ship 10x faster.
LLM Fluency: Familiarity with LLM orchestration, prompt engineering, and the agentic AI landscape.

Location: Based in or willing to work in New York (This is an immediate, onsite/hybrid position).

Why Lyzr?

Jobright is your personal AI job search agent that transforms the job search process into a fast, expert-guided journey. They are seeking an AI Engineer to build and scale business-facing AI agents, managing the entire lifecycle from prototype to production.

Why Join Us
• Build real, production AI agents used by real users
• High ownership and impact
• Work at the intersection of AI, agents, and product
• Shape how people experience AI-driven job search

Responsibilities
• Design, build, and deploy end-to-end AI agents for business and user-facing applications
• Develop agent-driven applications, including user interaction flows and APIs
• Build and maintain agent infrastructure, including orchestration, monitoring, and reliability
• Implement and iterate on agent evaluation (quality, reliability, latency, cost)
• Collaborate closely with product and business teams to translate real problems into agent solutions
• Continuously improve agent performance using real-world feedback and data

Qualification

Required
• Familiarity with at least one programming language (e.g. Python, JavaScript, TypeScript)
• Experience with writing a lot of code, backend or full-stack
• Experience building applications
• Strong interest in AI agents and applied LLM systems
• Ability to own features end-to-end, from design to production

Preferred
• Hands-on experience using and deploying AI agents, such as: Claude Code, Codex, ClawdBot, OpenCode, or similar agent frameworks/tools
• Experience with agent orchestration, tooling, or infra
• Experience building production AI products rather than demos
• Experience in fast-moving startup environments
• Product-minded approach and comfort with ambiguous problems