AI Engineer

• Collaborate with the CTO, AI consultant, and development team to design and deploy robust, scalable AI/ML architectures
• Develop, train, and maintain AI models, data pipelines, and integrations with APIs, databases, and SaaS platforms
• Experiment with new LLMs, embeddings, vector databases, and orchestration frameworks (e.g., LangChain, Semantic Kernel, or similar)
• Lead hands-on development/ prototyping of LLM-based applications, intelligent agents, and automation workflows
• Define AI architecture standards, establish model governance, and contribute to the long-term AI strategy in collaboration with the CTO
• Partner with business and technical leaders to translate strategic AI goals into actionable engineering initiatives
• Design systems for high availability, scalability, and efficient deployment in cloud environments (Azure, AWS, or GCP)
• Create technical documentation, architecture diagrams, and playbooks for deployment and scaling of AI solutions
• Participate in code reviews, mentor junior developers, and foster a culture of innovation and excellence in AI engineering
• Stay at the forefront of emerging AI frameworks, APIs, and tools, bringing forward practical innovations to enhance products and systems

• Embed directly with BIG's most strategic enterprise customers to design, build, and ship production AI applications powered by Claude
• Deliver technical artifacts including MCP servers, sub-agents, agent skills, and evaluation frameworks used in real customer workflows
• Lead rapid prototyping and proof-of-concept engagements that demonstrate tangible business impact from day one
• Act as the primary technical contact on-site, coordinating across BIG delivery, sales, and Anthropic partner teams
• Design scalable, enterprise-grade AI architectures leveraging Claude API, Claude Code, and Claude for Enterprise
• Advise customers on agentic workflow design, multi-agent orchestration, RAG patterns, evaluation frameworks, and LLM deployment at scale
• Translate complex customer requirements into architecture blueprints and technical roadmaps that align with business goals
• Identify and mitigate technical risks early in engagements to set delivery teams up for success
• Guide integration of Anthropic solutions with cloud hyperscalers (AWS, Azure, GCP) and enterprise data stacks
• Partner with Account Executives throughout the sales lifecycle to develop winning technical strategies for Anthropic-powered solutions
• Lead technical discovery workshops to uncover customer business objectives, current-state architecture, and AI readiness
• Build and deliver compelling demos, prototypes, and POCs that showcase Claude's capabilities for specific customer use cases
• Respond to RFPs, RFIs, and security questionnaires with clear, accurate, and persuasive technical content
• Translate complex AI concepts into business value for both technical teams and executive stakeholders
• Serve as an internal expert on the Anthropic Claude ecosystem — enabling the broader team through knowledge sharing and documentation
• Contribute reusable demo assets, accelerators, architecture playbooks, and prompt engineering guides
• Represent BIG at customer events, webinars, and Anthropic partner activities
• Provide structured field feedback to Anthropic product and partner teams to help shape roadmap direction

AI Engineer, Anthropic Architect – FDE

AI Engineer – Anthropic Architect

• Embed directly with BIG's most strategic enterprise customers to design, build, and ship production AI applications powered by Claude
• Deliver technical artifacts including MCP servers, sub-agents, agent skills, and evaluation frameworks used in real customer workflows
• Lead rapid prototyping and proof-of-concept engagements that demonstrate tangible business impact from day one
• Act as the primary technical contact on-site, coordinating across BIG delivery, sales, and Anthropic partner teams
• Design scalable, enterprise-grade AI architectures leveraging Claude API, Claude Code, and Claude for Enterprise
• Advise customers on agentic workflow design, multi-agent orchestration, RAG patterns, evaluation frameworks, and LLM deployment at scale
• Translate complex customer requirements into architecture blueprints and technical roadmaps that align with business goals
• Identify and mitigate technical risks early in engagements to set delivery teams up for success
• Guide integration of Anthropic solutions with cloud hyperscalers (AWS, Azure, GCP) and enterprise data stacks
• Partner with Account Executives throughout the sales lifecycle to develop winning technical strategies for Anthropic- powered solutions
• Lead technical discovery workshops to uncover customer business objectives, current-state architecture, and AI readiness
• Build and deliver compelling demos, prototypes, and POCs that showcase Claude's capabilities for specific customer use cases
• Respond to RFPs, RFIs, and security questionnaires with clear, accurate, and persuasive technical content
• Translate complex AI concepts into business value for both technical teams and executive stakeholders
• Serve as an internal expert on the Anthropic Claude ecosystem — enabling the broader team through knowledge sharing and documentation
• Contribute reusable demo assets, accelerators, architecture playbooks, and prompt engineering guides
• Represent BIG at customer events, webinars, and Anthropic partner activities
• Provide structured field feedback to Anthropic product and partner teams to help shape roadmap direction

• Overseeing the deployment, integration, and ongoing operational management of AI technologies across the organization
• Blending technical insight with strong operational management to ensure AI systems run efficiently
• Creating scalable and highly reliable software systems to support AI development and production operations in a multi-cloud environment
• Guiding the full lifecycle of AI initiatives—from initial deployment through optimization and continuous improvement
• Working cross-functionally to ensure AI capabilities deliver measurable business value
• Developing and executing operational strategies for managing and enhancing enterprise AI systems
• Establishing frameworks, best practices, and governance models to ensure consistent, ethical, and compliant AI operations
• Identifying and mitigating risks associated with AI deployment, model behavior, and system dependencies
• Managing the rollout of AI system updates, model retraining cycles, and platform upgrades
• Ensuring high availability, reliability, and scalability of AI systems across business units
• Leading and mentoring cross-functional teams involved in AI operations, engineering, and support

Senior Manager, AI Engineering Operations

• Take end-to-end ownership of key product outcomes, including platform adoption, user engagement, scalability, and business impact
• Serve as the primary liaison between engineering, stakeholders, customers, and internal production teams to ensure strong alignment
• Define and evolve core product experiences, including personalized workspaces, intelligent agents, automated workflows, and contextual artifacts
• Specify requirements that enable users to deploy custom tools and automations using natural language
• Ensure best-in-class integration with Autodesk and third-party products and services used in studio pipelines
• Drive data-informed prioritization
• Clearly communicate complex AI concepts and workflows to both technical and creative audiences

Senior Product Manager, Media & Entertainment AI Platform

• Own the technical architecture of the XR Training Academy platform
• Define and maintain architecture standards across frontend, backend, AI, cloud, and Unity integrations
• Create technical roadmaps aligned with product goals
• Lead technical planning and solution design sessions
• Review technical approaches and ensure alignment with business requirements
• Prevent over-engineering and unnecessary technical complexity
• Design scalable cloud-native architectures
• Define APIs, integration patterns, and service boundaries
• Ensure performance, security, maintainability, and scalability considerations are built into solutions
• Guide AI architecture and integration decisions
• Evaluate and recommend technology choices
• Translate product requirements into technical implementation plans
• Break epics and features into technical workstreams
• Define acceptance criteria and technical success metrics
• Identify technical risks and mitigation strategies
• Support estimation and sprint planning activities
• Guide the implementation of AI-powered experiences
• Evaluate and integrate LLMs, AI services, and agent-based workflows
• Establish best practices for AI architecture, prompting, evaluation, and governance
• Coach team members on the effective use of AI-assisted development
• Contribute production-quality code
• Build backend services, APIs, integrations, and cloud infrastructure
• Support frontend and platform development as required
• Review pull requests and mentor developers
• Troubleshoot technical issues and support delivery teams
• Foster strong communication and accountability

Technical Lead, Full-Stack, AI Platforms

• Pipeline Development: Build and execute outbound sequences targeting senior decision-makers.
• Qualification: Run discovery calls to separate real opportunities from the noise.
• Strategy: Work with the founders to refine our ICP and messaging based on real-world feedback.
• Stack Optimization: Leverage modern tooling (Clay, Sales Nav, etc.) to automate the manual parts of prospecting so you can focus on the strategy.

Business Development, AI Platform

• Lead the migration of a legacy front-end from vanilla JavaScript / jQuery / HTML5 / CSS to a modern React-based stack.
• Help maintain and enhance an existing Angular CLI front-end on a separate product.
• Develop overall concepts for new and existing product features and components across our AI-powered product portfolio.
• Contribute to back-end services in Python (agent workflows) and Node.js as priorities shift.
• Write production-ready, secure, and performant code, and apply secure coding practices throughout design and delivery.
• Own your work end-to-end through our CI/CD pipeline on GitLab — branching, merge requests, code review, build, test, and deploy — and track delivery in Jira.

Senior Full Stack AI Developer

• You'll manage and scale paid campaigns across Meta, TikTok, and Google — and help expand into newer channels like Reddit, Snapchat, and Quora.
• Day to day that means setting up and optimizing campaigns, translating performance data into creative briefs, keeping reporting accurate and up to date, and flagging what's working and what isn't.
• If you study ads while scrolling, save hooks that catch your eye, and naturally think about why certain creatives convert — this role was built for you.

Performance Marketer, Paid Acquisition

• Build and deliver AI solutions: Take ownership of developing high-performance AI features to help users detect, triage, and resolve incidents using observability data and tools.
• Rapid experimentation and iteration: Implement a highly iterative process where you quickly prototype, test, and validate with real users, including shipping and evolving LLM- or agent-powered workflows for incident lifecycle management and automated analysis tasks.
• Collaborate cross-functionally: Work with data analysts, product managers, and designers to shape AI-driven product features, including integration of agentic components with internal tools, alerting systems, runbooks, and developer workflows.
• Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows.
• Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams.
• Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.

Senior AI Engineer – Grafana Ops, AI/ML

• Translate business, data, and workflow problems into structured solutions and drive delivery end to end
• Design, build, and deploy AI-powered applications, models, dashboards, and automation tools
• Partner with trading, sales, risk, finance, operations, and technology teams to identify priorities and deliver measurable impact
• Apply strong engineering discipline, including testing, version control, monitoring, and iteration based on feedback and usage
• Communicate technical concepts and analytical findings clearly to both technical and non-technical stakeholders

Forward-Deployed AI Engineering Specialist

• Design and improve Paxos’s AI workflows. Own the prompt chains, agent patterns, structured-output schemas, evals, and test cases that power customer implementations.
• Turn reimbursement complexity into testable workflow logic. Translate payer rules, document requirements, clinical evidence standards, and operational edge cases into clear AI system behavior.
• Own AI quality and reliability. Analyze failures, improve prompts and schemas, and build evals that catch issues before they reach production.
• Work directly with customers during implementation. Clarify requirements, understand edge cases, and translate what we learn into workflows and reusable Paxos capabilities.
• Document how the system works. Write workflow specs, test plans, prompt/eval documentation, and implementation notes that help the team build and improve faster.

Founding AI Lead

• Embed directly with clients to discover operational pain points, map workflows, and identify high-ROI opportunities for AI and automation.
• Design and build AI agents using frameworks such as LangChain, LangGraph, AutoGen, or similar, including tool-use, memory, and multi-agent orchestration patterns.
• Develop AI-powered workflows that integrate with clients' existing systems (CRMs, ERPs, cloud platforms, communication tools, etc.)
• Engineer automation solutions across areas such as document processing, data extraction, reporting, customer communication, and internal operations.
• Own the full delivery lifecycle from scoping and architecture to build, testing, handoff, and lightweight documentation.
• Train and enable client teams to maintain and iterate on solutions post-deployment.
• Serve as a trusted technical advisor, translating complex AI capabilities into clear business value for non-technical stakeholders.
• Contribute internally by codifying reusable components, playbooks, and delivery templates that scale across the practice.

• Develop and operate scalable AI applications from backend logic, prioritizing security and operational excellence.
• Apply agentic programming practices to develop new and improved AI-powered features for the application, including refactoring existing codebases to be LLM-based or AI-assisted.
• Contribute to technology roadmap discussions to translate business requirements into autonomous, functional solutions.
• Write, debug, and troubleshoot code using widely adopted open-source AI technologies and maintain the codebase of a data analysis and validation platform.
• Work with cloud-based technologies and solutions.
• Capture requirements and refine them within multidisciplinary teams.
• Actively tackle problems and set priorities as needed.
• Ensure system validation and ongoing application support.
• Diagnose and resolve performance issues.
• Document code and processes so other developers can easily take over.
• Work with teams to integrate our systems with existing internal systems.
• Triage product- or system-related issues and debug, track, and resolve problems by analyzing their root causes and their impact on operations and network or service quality.

• Design and implement enterprise Generative AI services and knowledge copilots.
• Build retrieval‑augmented generation (RAG) pipelines leveraging enterprise data.
• Implement enterprise semantic search, knowledge indexing, and document intelligence systems.
• Develop reusable frameworks for enterprise prompt management, evaluation, and AI observability.
• Design and deploy AI agents capable of planning and executing multi‑step workflows across enterprise systems.
• Implement multi‑agent orchestration architectures where specialized agents collaborate to complete business tasks.
• Enable AI agents to interact with internal APIs, databases, and business applications while maintaining governance controls.
• Integrate AI systems with enterprise data platforms including Snowflake and its AI capabilities such as Snowflake Cortex.
• Implement AI guardrails, safety filters, and governance controls for enterprise GenAI usage.
• Design human‑in‑the‑loop review workflows for critical insurance decisions.
• Ensure compliance with privacy, security, and regulatory requirements.
• Monitor AI and agent outputs for reliability, bias, and quality.
• Provide technical leadership in the adoption of GenAI and Agentic AI across the enterprise.
• Partner with enterprise architecture and data teams to define AI platform standards.
• Mentor engineers and contribute to reusable enterprise AI frameworks.
• Help scale GenAI adoption across multiple business units.

Senior GenAI Engineer

• Bridge the gap between theoretical AI research and practical business applications by building end-to-end LLM-powered features.
• Optimize retrieval-augmented generation (RAG) pipelines and ensure the reliability of AI services in a cloud-native environment.
• Design and deliver production applications using model APIs (OpenAI, Anthropic, Gemini) and orchestration frameworks like LangChain, LlamaIndex, or LangGraph.
• Build and optimize retrieval systems over proprietary data using vector databases such as Pinecone, Weaviate, or Milvus and hybrid search techniques.
• Develop autonomous agents and multi-step reasoning workflows that call external tools and maintain state to solve complex automation tasks.
• Establish evaluation pipelines (using frameworks like DeepEval) to measure model drift, accuracy, and latency, ensuring safe and ethical AI outputs.
• Package AI applications in Docker containers and manage scalable deployments on cloud platforms (AWS, Azure, or GCP) using CI/CD pipelines.
• Design pipelines for data ingestion, cleaning, and chunking to support retrieval and model fine-tuning.

• Build and maintain backend services that support agent execution, orchestration, and lifecycle management
• Develop systems for workflow coordination, state management, and tool integration
• Write high-quality, maintainable code in Python to power platform capabilities and APIs
• Deploy and operate services on Kubernetes, ensuring reliability and scalability
• Contribute to systems for observability, logging, tracing, and debugging of distributed workflows
• Improve system performance across latency, throughput, and fault tolerance
• Build internal tools and APIs that improve the developer experience for teams using the platform
• Collaborate with engineers, product managers, and AI teams to deliver production-ready solutions
• Participate in design discussions and contribute to system architecture and technical decisions

Software Engineer – Senior Software Engineer, AI Platform

• IKS Health is seeking a Senior AI Engineer to design and build modern, AI‑first applications across web and mobile platforms.
• Build and maintain AI‑first web and mobile applications using modern frameworks and best‑in‑class engineering practices.
• Develop AI‑powered features using Python, LangGraph, and modern LLM tooling.
• Create end‑to‑end solutions across front end, back end, APIs, and cloud infrastructure.
• Write clean, scalable code in TypeScript (Node), JavaScript (React), and Python using established design patterns.
• Work closely with cross‑functional teams to define, design, and ship new features with strong ownership of outcomes.

Director, Senior AI Engineer

• Architect, build, and maintain AI‑first web and mobile applications using modern frameworks and engineering best practices.
• Lead the development of AI‑powered features using Python, LangGraph, and modern LLM tooling.
• Design and implement agentic workflow applications, including orchestration, tool use, stateful flows, and human‑in‑the‑loop patterns.
• Develop end‑to‑end solutions across the front end, back end, APIs, and cloud infrastructure.
• Write clean, scalable, and maintainable code in TypeScript (Node), JavaScript (React), and Python using established design patterns.
• Optimize applications for speed, scalability, reliability, and long‑term maintainability.
• Work closely with cross‑functional teams to define, design, and ship new features with strong ownership of outcomes.
• Provide architectural guidance, code reviews, and mentorship to engineering teams.
• Partner with clients to lead demos, support rollout discussions, and ensure successful adoption of AI‑powered solutions.

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AI Engineer

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AI Engineer – Anthropic Architect

AI Engineer – Anthropic Architect

Senior Manager, AI Engineering Operations

Senior Product Manager, Media & Entertainment AI Platform

Technical Lead, Full-Stack, AI Platforms

Business Development, AI Platform

Senior Full Stack AI Developer

Performance Marketer, Paid Acquisition

Senior AI Engineer – Grafana Ops, AI/ML

Forward-Deployed AI Engineering Specialist

Founding AI Lead

AI Engineer

AI Engineer

Senior GenAI Engineer

AI Engineer

Software Engineer – Senior Software Engineer, AI Platform

Director, Senior AI Engineer

Associate Director, AI Architect