Forward Deployed Application/ML Engineering Expert

What you Bring

• Extensive hands-on experience in software and application engineering for cloud-native, enterprise, and SaaS environments, with strong knowledge of architectural principles such as scalability, security, and reliability.
• Proven ability to design and deliver AI-native applications, utilizing large language models, RAG architectures, vector databases, and agentic systems to innovate enterprise workflows.
• Strong proficiency in widely used AI/ML Python libraries and frameworks
• Exposure to data pipelines and MLOps practices
• Skilled in integrating Agentic AI into complex business processes, ensuring responsible and effective use of AI agents within enterprise operations.
• Solid architectural foundation across cloud platforms, distributed systems, scalability, security, and reliability.
• Experience owning solutions across the full application lifecycle, from design and implementation to deployment and production operations.
• Ability to work effectively with cross functional teams and customer stakeholders, communicating complex technical topics clearly.
• Learning mindset, technical leadership, and accountability in high impact, ambiguous environments
• You demonstrate a proactive approach to leveraging AI in everyday workflows, ensuring high‐quality outputs through thoughtful context design and system integration
• What you Build
• In this role, you will:
• Design, develop, and operate production‐grade, cloud‐native enterprise applications integrating AI capabilities such as large language models, retrieval‐augmented generation, and agent‐based workflows.
• Embed directly into customer projects and fast moving cross functional teams to rapidly understand business processes, technical landscapes, and operational challenges.
• Translate business and product requirements into robust application architectures, balancing speed, quality, security, and long‐term maintainability.
• Rapidly prototype, iterate, and productionize solutions in customer environments, adapting reference architectures and reusable assets to real world enterprise constraints.
• Own application delivery end‐to‐end, from problem framing and prototyping through deployment, observability, and production operations.
• Apply AI‐assisted engineering practices, evaluation frameworks, and architectural guardrails to ensure compliant, trustworthy, and high‐quality solutions.