AI Development Engineer
New
P
Proximity WorksTechnology Consulting
IndiaContractMiddle
Salary not disclosed
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Job Details
- Required Skills
- MicroservicesPrompt Engineering
Requirements
- Strong software engineering fundamentals and hands-on experience building production-grade systems.
- Experience in one or more modalities such as vision, images, video, text, audio, or speech.
- Deeper knowledge and hands-on experience with LLMs, VLMs, multimodal AI systems, and foundation model architectures.
- Ability to actively find, read, understand, and implement ideas from AI research papers.
- Experience building or integrating agentic applications, AI copilots, RAG systems, workflow automation, or multimodal GenAI systems.
- Strong understanding of system design, APIs, data flows, testing, observability, security, and production reliability.
- Practical experience with prompt engineering, context engineering, model evaluation, benchmarking, and AI workflow orchestration.
- Ability to convert ambiguous requirements into structured specs, implementation plans, and validation frameworks.
- Strong debugging, problem-solving, communication, ownership, and learning agility.
Responsibilities
- Translate ambiguous product or business requirements into clear technical specifications, system designs, and validation plans.
- Build, maintain, and scale AI-powered production systems and agentic applications.
- Design workflows where LLMs, VLMs, tools, APIs, retrieval systems, and traditional microservices work together reliably.
- Use AI-assisted development tools while maintaining code quality, security, performance, and long-term maintainability.
- Prevent AI-generated code bloat, dead code, and unnecessary complexity.
- Build observability, evaluation, testing, and monitoring systems for AI-generated outputs.
- Optimize prompts, model selection, workflows, and inference cost.
- Apply Responsible AI principles including safety, privacy, fairness, transparency, and accountability.
- Work with cross-functional teams across product, engineering, security, data, and design.
- Mentor engineers to move from implementation-heavy development to system orchestration and AI-first engineering practices.
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