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Tier-1 brand plus popular mid-level AI engineering role with broad requirements increases applicant competition.
Specialized AI production and LLM skills are moderately transferable across industries.
Multiple mandatory technical skills and production AI experience required, causing strict shortlisting.
Design and deploy AI-powered features (LLMs, RAG, agents, ML APIs) integrated into existing services across backend, frontend, and data science workflows.
Ensure AI service production reliability including performance (latency, throughput), cost optimization, observability, and rollback/versioning mechanisms.
Implement safety and compliance measures for AI features (prompt injection defenses, PII handling, abuse controls) and contribute to internal AI tooling for reuse and acceleration.
Strong software engineering skills in Python plus one of Node.js, Java, or Go.
Experience building and shipping at least one AI-powered product to production (e.g., search, chatbots, recommendations).
Practical knowledge of LLM concepts including prompts, context engineering, embeddings, vector search, and evaluation metrics.
Familiarity with integration of third-party AI providers (OpenAI, Anthropic) and agentic frameworks like Langraph.
Experienced in designing and operating microservices and APIs in cloud infrastructure environments.
Ability to collaborate closely with data science teams to productionize trained models as stable APIs.
Strong focus on operationalizing AI features with safety, security, observability, and cost/latency trade-offs in mind.