Accountabilities:
The Forward Deployed AI Engineer will act as a technical leader responsible for designing, building, and deploying AI solutions directly with enterprise customers. This role requires strong engineering capabilities, customer collaboration skills, and the ability to translate business challenges into scalable AI applications. Develop full-stack AI and machine learning applications that demonstrate practical solutions for enterprise use cases. Work directly with customer teams to move AI and agentic applications from early prototypes to production-ready systems. Design technical solutions, architecture approaches, and deployment strategies aligned with customer objectives. Advise customer stakeholders on AI adoption strategies, roadmaps, and implementation best practices. Build scalable AI/ML systems using modern frameworks, tools, and enterprise-grade engineering practices. Create reusable solution patterns, reference architectures, starter kits, and internal playbooks to support broader adoption. Collaborate with product and engineering teams by sharing customer insights and improving AI capabilities. Act as a subject matter expert and mentor teams on AI engineering practices and emerging technologies. Support the development of innovative approaches for enterprise AI transformation. Contribute to technical documentation, knowledge sharing, and continuous improvement initiatives. Requirements: The ideal candidate is a senior engineering professional with strong experience building production-grade systems and applying AI/ML technologies to solve complex problems. You should have a combination of software engineering expertise, machine learning knowledge, and the ability to collaborate directly with enterprise customers. 7+ years of experience building and deploying production-grade software systems. 2–4 years of hands-on experience developing machine learning systems, Generative AI applications, or agentic AI solutions. Strong software engineering, data engineering, and applied AI/ML capabilities. Proven experience building full-stack ML applications or AI-powered systems using modern frameworks and tooling. Experience designing scalable solutions and working with enterprise technology environments. Strong problem-solving skills and ability to translate business requirements into technical solutions. Excellent communication skills with the ability to collaborate with technical and business stakeholders. Nice to have: Experience with MLOps frameworks, LLM orchestration, and modern AI technologies such as LangChain, LlamaIndex, vLLM, Ray, or MLflow. Hands-on experience with vector databases and Retrieval-Augmented Generation (RAG) architectures. Background in technical consulting, solution architecture, or customer-facing engineering roles. Familiarity with distributed data platforms such as Apache Spark, Iceberg, or Kubernetes. Experience working with enterprise AI deployment strategies and production-scale applications. Benefits: Remote work flexibility. Generous paid time off policy. Dedicated company-wide unplugged days to support work-life balance. Mental and physical wellness programs. Phone and internet reimbursement program. Access to ongoing career development opportunities. Competitive compensation and comprehensive benefits package. Paid volunteer time initiatives. Employee resource groups and inclusive workplace programs. Opportunity to work on impactful AI projects with enterprise customers.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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