Sr. Software Development Engineer, Oisl

Amazon Amazon · Big Tech · Redmond, WA · Software Development

Senior Software Development Engineer to lead the design, development, and deployment of AI agentic solutions and large-scale data pipelines for Amazon Leo's satellite network systems. The role involves building LLM-powered autonomous agents, RAG pipelines, and tool-use frameworks, alongside optimizing data processing for telemetry, manufacturing, and operational data. A strong emphasis is placed on security-first design and technical leadership.

What you'd actually do

  1. Define the architecture for scalable data engineering platforms and AI agentic pipelines that process ground production data, satellite telemetry, network events, and on-orbit operational data at scale — with security built into every layer from the ground up
  2. Design, build, and deploy LLM-powered autonomous agent systems (multi-agent orchestration, RAG pipelines, tool-use frameworks) for intelligent automation — including investigation, triage, and remediation workflows
  3. Build and optimize large-scale data pipelines (batch and streaming) using technologies such as Apache Flink, Spark, Kafka, and AWS-native services (Kinesis, Glue, S3, Redshift, OpenSearch)
  4. Champion a security-first engineering culture — embed threat modeling, least-privilege access, encryption in transit/at rest, secure coding practices, and defense-in-depth principles into system design from day one
  5. Partner with Networking, Operations, and Data Science teams to identify opportunities for AI-driven automation and drive adoption of intelligent tooling

Skills

Required

  • 5+ years of non-internship professional software development experience
  • 5+ years of programming with at least one software programming language experience
  • 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience as a mentor, tech lead or leading an engineering team
  • Bachelor's degree in Computer Science, Computer Engineering, or a related technical field
  • 3+ years of experience with data engineering (ETL/ELT pipelines, data warehousing, streaming architectures)
  • Strong proficiency in at least one systems language (Java, Python, Go, Rust, or C++)
  • Experience with AWS services (EC2, S3, Lambda, Step Functions, Kinesis, DynamoDB, or equivalent)
  • Experience with CI/CD pipelines and infrastructure-as-code (CDK, CloudFormation, Terraform)
  • Demonstrated security-first mindset: experience applying threat modeling, secure design patterns, and defense-in-depth to production systems

Nice to have

  • 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Master's degree or PhD in Computer Science, Machine Learning, Data Science, or related field
  • Experience building LLM-based agentic systems (autonomous agents, multi-agent frameworks, tool-use patterns, RAG)
  • Experience with ML/AI pipeline orchestration (SageMaker, Bedrock, or similar platforms)
  • Experience with streaming data technologies (Apache Flink, Kafka Streams, Kinesis Data Analytics)
  • Experience with graph databases or knowledge graphs
  • Track record of technical leadership: writing design documents, leading architecture reviews, defining team technical roadmaps
  • Familiarity with satellite/telecommunications systems or IoT-scale data processing
  • Experience with security practices such as zero-trust architectures, identity & access management, encryption frameworks, or compliance automation
  • Active security clearance or ability to obtain one

What the JD emphasized

  • security-first mindset
  • security built into every layer from the ground up
  • LLM-powered autonomous agent systems
  • multi-agent orchestration
  • RAG pipelines
  • tool-use frameworks
  • large-scale data pipelines
  • satellite-network scale

Other signals

  • LLM-powered autonomous agent systems
  • multi-agent orchestration
  • RAG pipelines
  • tool-use frameworks
  • large-scale data pipelines
  • satellite-network scale