AI/ML & Forward Deployed Engineer

About the role

This position offers the opportunity to build and deploy high-impact AI, machine learning, and generative AI solutions from initial concept through production. You will combine software engineering, machine learning, and MLOps/LLMOps expertise to create scalable and reliable AI products.

Responsibilities

• Solve complex business problems through technologies such as LLMs, RAG pipelines, NLP, forecasting, and anomaly detection.
• Work across the full AI lifecycle, from experimentation and evaluation to deployment, monitoring, and continuous improvement.
• Ensure AI solutions meet enterprise requirements for data quality, governance, security, role-based access control, encryption, and auditability.
• Collaborate with business and technical stakeholders to understand requirements, identify opportunities for AI adoption, and translate them into effective technical solutions.
• Support solutions through production operations, troubleshooting, optimization, and ongoing improvements.

Requirements

• 8+ years of professional software engineering or technical engineering experience.
• Strong hands-on experience in Machine Learning and AI/ML Engineering.
• Advanced Python development skills and practical experience with deep learning and machine learning techniques.
• Experience with NLP, forecasting, classification, regression, and anomaly detection.
• Proven experience building GenAI applications using LLMs and Retrieval-Augmented Generation (RAG) architectures.
• Strong understanding of embeddings, retrieval tuning, reranking, prompt engineering, and AI/LLM evaluation methodologies.
• Solid knowledge of MLOps and LLMOps principles and practices across the AI development lifecycle.
• Hands-on experience with Docker, Kubernetes, and CI/CD technologies for production deployments.
• Experience designing and developing REST and gRPC APIs and event-driven services.
• Knowledge of model monitoring, model versioning, drift detection, performance evaluation, and model lifecycle management.
• Strong understanding of data quality, data governance, security controls, RBAC, encryption, and audit trails.
• Ability to work effectively with both technical and non-technical stakeholders and translate business challenges into practical AI solutions.
• Strong problem-solving, analytical, communication, and collaboration skills.
• Ability to operate effectively in fast-moving environments while balancing experimentation with production reliability.

Benefits

Competitive annual salary of $100,000–$120,000.
Full-time opportunity with a remote working model.
Opportunity to work on cutting-edge AI, machine learning, and GenAI solutions.
Hands-on exposure to LLMs, RAG, MLOps, LLMOps, Kubernetes, and cloud-native engineering practices.
Opportunity to contribute to AI solutions from concept and experimentation through production deployment.
Work on technically challenging projects with a strong focus on scalability, security, governance, and observability.
Collaborative environment with opportunities to engage directly with stakeholders and influence AI solution strategy.
Opportunity to expand expertise across modern AI engineering, machine learning, and production software development.