Applied AI Engineer

Nexxa.ai is building artificial super intelligence for heavy industries — enabling machines, systems and operations to think, decide and act autonomously across manufacturing, large-scale infrastructure, logistics and legacy environments.
Our mission is to translate deep technical breakthroughs into operational reality, solving some of the hardest systems-level problems in industry.

We’re looking for Applied AI Engineers to work as forward deployed directly with customers and lead the end-to-end delivery of high-impact technical solutions. You’ll embed deeply with customer teams, translating real-world challenges into production-ready systems that leverage Generative AI, Computer Vision, and Machine Learning.

This role is a blend of software engineering, ML engineering, architecture, and consulting. You’ll design and deploy solutions, integrate models, build custom workflows, and guide customers through successful implementation. This position requires frequent travel to customer sites.

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  Engage directly with enterprise and strategic customers to understand their workflows, data, and technical requirements.

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  Architect, build, and deploy custom solutions leveraging GenAI, LLMs, Machine Learning and Vision models, and customer data sources.

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  Lead full project lifecycles: scoping, solution design, development, implementation, testing, deployment, and iteration.

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  Integrate and optimize AI/ML pipelines, including data preprocessing, prompt engineering, model selection, and evaluation.

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  Build reliable, scalable software integrations using APIs, cloud services, and containerized systems.

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  Troubleshoot complex technical issues across the stack—applications, models, data pipelines, infrastructure, and integrations.

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  Act as the customer’s trusted technical advisor, enabling adoption of new product capabilities and AI features.

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  Partner closely with internal product and engineering teams to communicate customer feedback and shape roadmap direction.

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  Produce high-quality documentation, architecture diagrams, runbooks, and technical assets for customer teams.

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  Mentor junior engineers and contribute to internal best practices for FDE delivery.

• 5–10+ years in engineering roles such as Forward Deployed Engineer, ML Engineer, Software Engineer, Solutions Engineer, Technical Consultant, or similar.

• Strong proficiency in Python, JavaScript/TypeScript, Go, or similar production-oriented languages.

• Hands-on experience with Machine Learning, including training, fine-tuning, evaluating, or deploying models.

• Direct experience with Generative AI (LLMs, multimodal models) and applying them to real-world problems.

• Exposure to Computer Vision techniques (detection, segmentation, OCR, embeddings, multimodal pipelines).

• Strong knowledge of ML frameworks (PyTorch, TensorFlow, OpenCV, etc.).

• Experience with cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes).

• Excellent communication skills with both technical and non-technical audiences.

• Comfort leading customer-facing engagements and guiding stakeholders through ambiguity.

• Willingness and ability to travel frequently.

• Prior experience in consulting, technical solutions, professional services, or customer-embedded technical roles.

• Experience with vector databases, embedding pipelines, or retrieval-augmented generation (RAG).

• Experience building APIs, microservices, or distributed systems.

• Familiarity with MLOps tools (Docker, Kubernetes, model registries, CI/CD for ML).

• Background in deploying or fine-tuning CV models (YOLO, SAM, CLIP, DETR, etc.).

• Experience in startup or high-growth environments.

• A customer-obsessed senior engineer who thrives in deeply technical, fast-moving environments.

• A creative problem solver who can translate vague requirements into robust, scalable solutions.

• Someone excited to combine software engineering with real-world AI deployments.

• A leader who can own outcomes end-to-end and influence both customer and internal teams.