Azure AI Engineer
Implement and deploy end-to-end enterprise AI solutions and RAG pipelines on the Azure stack. Establish AI guardrails, observability, and CI/CD pipelines to ensure secure and compliant production-ready AI services.
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Implement and deploy end-to-end enterprise AI solutions and RAG pipelines on the Azure stack. Establish AI guardrails, observability, and CI/CD pipelines to ensure secure and compliant production-ready AI services.
The role involves joining a talent database to be matched with software development opportunities for various global clients. You will provide expert-level AI engineering services while maintaining a professional and agile development process.
Research frontier AI systems and develop datasets, experiments, prototypes, tools, and evaluation frameworks across areas such as reinforcement learning, post-training, synthetic data, and AI agents. Analyze results rigorously and collaborate across teams to turn validated research into scalable products and share findings with the research community.
Lead and manage the development of innovative software solutions while driving delivery excellence through strategic leadership and hands-on technical involvement. Collaborate cross-functionally to optimize platform features and foster a high-performing engineering team.
Design, train, and deploy machine learning and LLM-based guardrail models to ensure safety and mitigate risks across Atlassian products. Collaborate with cross-functional teams to build evaluation frameworks and optimize real-time serving for high-throughput production workloads.
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You will scope customer environments, prototype AI-powered solutions, and harden them into production-grade deployments. The role involves regular travel to customer sites to lead discovery, prototyping, and go-live phases.
Modernize enterprise infrastructure operations by implementing an automation-first, AI-assisted operating model across endpoint, identity, and cloud platforms. Lead the architecture and integration of automated workflows for endpoint management, identity lifecycle, and security remediation.
You will be responsible for creating reusable, production-grade feature data products to enable high-performing AI and machine learning solutions. This involves discovering and maintaining high-quality features while partnering with cross-functional teams to translate business challenges into scalable predictive capabilities.
Create engaging short-form video content optimized for social media performance. Develop and build automated agent workflows using AI coding tools to streamline video production.
Architect and deploy autonomous AI agents that execute workflows across sales, messaging, and operations. Partner with cross-functional teams to build scalable GenAI infrastructure and iterate on model performance using rigorous experimentation.
Provide technical support for database and AI-related issues, including troubleshooting, diagnostics, and performance tuning. Collaborate with engineering and product teams to resolve defects and contribute to technical documentation and knowledge bases.
You will build and implement practical AI research assets, including reinforcement learning environments and agentic systems. Additionally, you will develop evaluation harnesses and benchmarks to measure model performance, safety, and cost across various customer use cases.
The Forward Deployed AI Security Engineer will embed with client teams to assess, deploy, and operationalize AI security controls within production environments. They are responsible for designing secure control planes, performing adversarial testing, and producing high-quality technical documentation and executive briefings.
You will be responsible for creating reusable, production-grade feature data products to enable high-performing AI and machine learning solutions. This involves discovering and maintaining high-quality features while partnering with cross-functional teams to translate business challenges into scalable predictive capabilities.
Design, develop, and deploy scalable AI-powered software systems to enhance real estate operations and product innovation. Collaborate with cross-functional teams to build and optimize agentic pipelines and integrate LLM-driven solutions into production environments.
The AI Platform Engineer designs, builds, and operates AI-powered systems to optimize revenue workflows across Sales, Marketing, and Customer Success. This role focuses on implementing production-grade AI agents and evaluation frameworks to ensure reliable, measurable business outcomes.
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You will own the end-to-end architecture of the agent harness, including the agent loop, memory, permissions, and orchestration layers. Additionally, you will build evaluation suites and ensure reliable tool use across various AI models.
You will build and maintain revenue systems, including CRM instrumentation, renewal automation, and quota modeling. Additionally, you will develop and manage AI agents to streamline growth and account management processes.
Design, develop, and maintain ServiceNow AIOps and Event Management solutions while ensuring adherence to best practices. Collaborate with stakeholders to implement integrations with monitoring tools and optimize platform capabilities for business-critical infrastructure.
You will design and build secure foundations for AI platforms, including identity, authorization, and policy-enforcement controls. Additionally, you will conduct threat modelling and adversarial testing to ensure AI systems are protected against threats like prompt injection and data leakage.
Design and build a centralized AI platform capability for knowledge representation, reasoning, and retrieval. Collaborate with product teams to implement reusable APIs and evaluation suites that ensure reliable, contextual AI-powered workflows.
Design, build, and operate a central AI services platform including model gateways, RAG-as-a-service, and observability tools. Partner with product engineering teams to onboard AI features and ensure high operational standards for production AI services.
The Forward Deployed Engineer will lead the technical design and implementation of large-scale agentic AI solutions for enterprise clients. They will own projects end-to-end, acting as the primary technical point of contact while building production-grade components and optimizing AI agent performance.
The consultant will design and implement scalable enterprise platform solutions across cloud, data, and AI-enabled workloads. They will lead cloud migration initiatives and drive AI-accelerated development by integrating modern tools into customer engineering workflows.
The Forward Deployed Engineer will act as a technical consultant to scope AI deliverables, review model outputs, and prototype solutions for clients. They are responsible for owning delivery outcomes and managing multiple workstreams in a fast-paced environment.
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Design, build, and deploy AI-powered Copilot agents and automated workflows to optimize healthcare revenue cycle management processes. Manage knowledge architecture, maintain SOPs, and train business users on AI adoption and productivity tools.
Design and own comprehensive testing strategies and evaluation frameworks for Generative AI products, including LLMs, RAG pipelines, and AI agents. Build automated evaluation pipelines and define measurable quality KPIs to ensure system reliability and safety.
Design and implement LLM-powered multi-agent systems to automate commerce operations and augment decision-making. Develop scalable .NET microservices and React frontends while ensuring safe agent behavior through guardrails and observability.
Lead the technical strategy and deployment of OpenAI solutions within the AWS ecosystem for high-priority enterprise customers. Develop repeatable architectural patterns and enable AWS partners to independently scale Generative AI adoption.
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