AI Development Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Acquire a profound understanding of technical requirements and system-level design to minimize rework and decrease AI-generated errors.

• Convert ambiguous product and business concepts into well-defined, structured technical specifications.

• Develop specifications that act as the definitive reference for engineering teams and AI systems.

• Implement practices aimed at reducing functional defects and operational challenges arising from AI-generated code.

• Detect and eliminate code bloat, redundant logic, dead code, and unnecessary complexity.

• Ensure that AI-generated code is comprehensible, maintainable, and easily navigable for engineers.

• Create documentation and engineering artifacts to prevent AI-generated code from becoming a black box.

• Integrate security best practices into prompts, context, and code-generation processes.

• Develop, maintain, and scale production systems utilizing Generative AI.

• Design and oversee agentic workflows where AI components interact with conventional microservices.

• Investigate methods to transition manual workflows into intelligent, agent-driven applications.

• Validate automated outputs for security, performance, reliability, and expected functionality.

• Introduce observability into services and systems to identify and resolve production issues.

• Research self-healing production workflows that leverage AI to analyze logs, detect issues, and propose real-time solutions.

• Optimize inference costs through prompt engineering, model selection, tool application, and workflow design.

• Balance model performance, token usage, and business return on investment.

• Mitigate technical debt and redundant implementations before they impact system performance or cloud expenses.

• Collaborate with Product, Production Engineering, Security, and other relevant stakeholders.

• Promote experimentation with AI workflows and foster continuous improvement.

• Mentor junior engineers and support the transition toward AI-assisted engineering and system orchestration.

⛳️ Requirements

• Solid foundations in Machine Learning and AI, encompassing linear algebra, probability and statistics, supervised and unsupervised learning algorithms, and standard MLP/DNN architectures.

• Comprehension of bias-variance trade-offs, model fitting and selection, hyperparameter tuning, and model performance assessment.

• 5+ years of practical experience and working knowledge of Generative AI foundation models and LLM building blocks.

• Understanding of transformers applicable to vision and text.

• Familiarity with tokenization and attention mechanisms.

• Knowledge of prompting techniques.

• Understanding of Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) concepts.

• Familiarity with Retrieval-Augmented Generation (RAG).

• Practical experience with PyTorch, TensorFlow, and Hugging Face.

• Experience in building or working on AI applications across multiple domains, including text, vision, speech, audio, and video.

• Capability to grasp complex engineering requirements and translate them into structured specifications, implementation strategies, and validation workflows.

• Strong problem-solving abilities and a keen interest in exploring how AI can enhance engineering workflows and application development.

🏝️ Benefits

• Competitive salary: We seek exceptional talent and offer appropriate compensation.

• Proximity Talks: Engage and learn from designers, engineers, product leaders, and AI experts.

• Continuous learning: Collaborate with a world-class team and stay updated on the latest advancements in AI, engineering, and product development.

• High-impact work: Develop AI-first systems and products utilized at scale by global clients.