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Specialized senior ML/AI role with niche agent/LLM skills but moderate local candidate pool.
Deep LLM, agent, and ML systems expertise required, limiting cross-industry transferability.
Explicit 10+ years requirement plus mandatory LLM, agent frameworks, cloud, and systems expertise.
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Architect, implement, and optimize advanced AI systems including LLMs, RAG pipelines, and multi-agent architectures for enterprise-scale environments.
Operationalize and manage agent lifecycle ensuring reliability, security, and performance at scale through practices like state management, monitoring, retraining, and rollback.
Collaborate cross-functionally with product, engineering, and research teams to integrate AI features delivering measurable business value, while applying Responsible AI governance and security controls.
10+ years of software development experience, including 3+ years specifically in AI/ML systems involving LLMs, RAG, and agent-based architectures.
Proficient in Python, C#, Angular/JavaScript, with hands-on experience using AI agent frameworks such as MCP, LangChain Agents, CrewAI, AutoGen, or A2A/ADK.
Strong cloud computing knowledge (AWS preferred; Azure or GCP acceptable) and experience with cloud-native services for AI workloads.
Bachelor’s or Master’s degree in Computer Science or Software Engineering required.
Experienced systems engineer skilled at integrating AI-driven agent architectures in distributed, microservices, and event-driven environments at enterprise scale.
Proficient in both development and operationalizing AI agents, familiar with DevOps practices like CI/CD and infrastructure-as-code for scalable, reliable deployments.
Able to translate business challenges into AI/ML solutions, influencing product direction through technical expertise and cross-functional collaboration.