About the role

Senior Forward Deployed Engineer at Nexxa.ai translating technical challenges into AI-powered solutions. Fostering relationships with customers while leading end-to-end project lifecycles with deep technical integration.

Responsibilities

Engage directly with enterprise and strategic customers to understand their workflows, data, and technical requirements.
Architect, build, and deploy custom solutions leveraging GenAI, LLMs, Machine Learning and Vision models, and customer data sources.
Lead full project lifecycles: scoping, solution design, development, implementation, testing, deployment, and iteration.
Integrate and optimize AI/ML pipelines, including data preprocessing, prompt engineering, model selection, and evaluation.
Build reliable, scalable software integrations using APIs, cloud services, and containerized systems.
Troubleshoot complex technical issues across the stack—applications, models, data pipelines, infrastructure, and integrations.
Act as the customer’s trusted technical advisor, enabling adoption of new product capabilities and AI features.
Partner closely with internal product and engineering teams to communicate customer feedback and shape roadmap direction.
Produce high-quality documentation, architecture diagrams, runbooks, and technical assets for customer teams.
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 (preferred).
Experience with vector databases, embedding pipelines, or retrieval-augmented generation (RAG) (preferred).
Experience building APIs, microservices, or distributed systems (preferred).
Familiarity with MLOps tools (Docker, Kubernetes, model registries, CI/CD for ML) (preferred).
Background in deploying or fine-tuning CV models (YOLO, SAM, CLIP, DETR, etc.) (preferred).

Innovative Environment: Play a critical role in transforming heavy industries through groundbreaking AI and automation technologies.
Collaborative Culture: Be part of a team that values innovation, discipline, and continuous improvement.
Professional Growth: Benefit from significant opportunities for career development and advancement.
Competitive Compensation: Enjoy a comprehensive salary and equity package reflective of your expertise and contributions.