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Known employer, mid-level backend+GenAI role, metro hiring and broad skillset create high competition.
Backend and cloud skills are transferable, but GenAI/LLM and RAG expertise require specialization.
Explicit 5–8 years plus mandatory backend, cloud, and AI/LLM experience tightens filtering.
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Lead and own the architecture, design, and delivery of scalable AI/ML-integrated backend systems including Generative AI solutions.
Drive end-to-end development lifecycle from analysis to deployment, focusing on AI-assisted tooling, LLM integrations, and agentic workflows.
Collaborate cross-functionally to define technical strategy, conduct code reviews, and ensure adherence to Agile practices within hybrid work setup.
5–8 years of software engineering experience with backend development using Python, Spark, Scala, Java, or Spring Boot.
3+ years experience building AI-integrated or LLM-backed services and cloud-native systems on AWS (Lambda, ECS, S3, API Gateway).
Experience with scalable software architectures involving RAG pipelines, vector stores, multi-agent orchestration, microservices, RESTful APIs, and messaging systems (Kafka, SQS).
Work Experience Required: 5–8 years; Hybrid work model requiring 2 days per week onsite.
Experienced in designing and deploying scalable AI-driven backend architectures, particularly with Generative AI and LLMs.
Familiar with DevSecOps, CI/CD, Docker, infrastructure-as-code, and MLOps or AI deployment workflows.
Proficient in Agile development environments with ability to lead technical discussions and cross-team collaboration.