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Senior Software Engineer – AI, LLMs

Full-stack EngineerSoftware EngineerFull TimeRemoteTeam 11-50H1B No SponsorCompany Site LinkedIn

Location

United States

Posted

15 days ago

Salary

$120K - $160K / year

6 yrs expEnglishAWSCloudDockerMicroservicesPostgre SQLPythonSQLTerraformType Script

Job Description

• Design and implement backend services that enable intelligent agent workflows and autonomous infrastructure actions • Develop APIs and orchestration layers in Python and TypeScript, integrating LLMs, vector databases, and observability pipelines • Build scalable systems to support LLM-based reasoning, retrieval, and decision-making across cloud infrastructure • Integrate with AWS Bedrock and other LLM platforms to support multi-model capabilities • Develop data access and semantic search layers using vector databases (e.g., pgvector, Pinecone, Qdrant) • Build robust monitoring, testing, and CI/CD systems to ensure reliability and reproducibility of AI workflows • Collaborate closely with Product and DevOps teams to design architecture diagrams, plan deployments, and monitor system health • Write clean, maintainable code with clear documentation and strong adherence to security and performance best practices • Participate in code reviews, design discussions, and iterative delivery cycles to improve product velocity and quality

Job Requirements

6+ years of backend engineering experience in production environments
Strong proficiency in Python and TypeScript for building distributed, event-driven systems
Deep understanding of AWS services (Lambda, ECS, Bedrock, S3, CloudWatch, etc.)
Experience designing APIs, microservices, and event pipelines that interface with LLMs or AI models
Familiarity with vector databases and concepts such as embeddings, similarity search, and retrieval-augmented generation
Experience with infrastructure-as-code tools such as Terraform or AWS CDK
Strong understanding of SQL and schema migration workflows (PostgreSQL or similar)
Hands-on experience with Docker, GitHub Actions, and cloud-native CI/CD workflows
Ability to diagram systems, communicate architecture decisions clearly, and work effectively in a distributed team
Strong ownership mindset and ability to deliver in fast-moving, ambiguous environments