Job Purpose/Summary
The Senior Platform Engineer will develop and implement the backend and data platform architecture for our next-generation space and critical infrastructure defense capabilities. They will build the services, APIs, distributed workers, and data-management components that ingest high-volume telemetry and derived data, and export/stream data for product, analytics, and machine learning UX.
This is a hands-on product development role, not a pure infrastructure operations position. Success in year one involves turning the approved architecture and data model into reliable production services spanning object storage, hot DBs, and data lake architecture, establishing stable Protobuf/gRPC interfaces and delivering secure, observable, cloud-native deployments that can support connected and air-gapped environments. They will influence implementation standards, technical tradeoffs, product delivery, and provide engineering leadership as the team grows.
Duties and Responsibilities
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Lead the development and implementation of core platform services
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Build versioned API and service contracts using Protobuf/gRPC
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Implement and maintain database schemas for data management and application state
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Implement and optimize ingest workflows for massive unstructured time-series and telemetry datasets
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Build horizontally scalable asynchronous workers and distributed job queues for data ingest and export
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Implement secure data upload, download, and object-management workflows
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Establish automated unit, integration, contract, load, and failure-mode testing, perform troubleshooting, quality assurance, and production support (SRE-lite)
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Implement platform observability, including log aggregation, metrics, engineering dashboards, alerting, and user-visible job status and error information
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Collaborate with frontend, machine learning, product and infrastructure teams
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Document APIs, data contracts, deployment procedures, runbooks, etc...
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Review code, mentor engineers, and ensure platform implementations comply with security requirements, industry standards, and company policies
Qualifications
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5+ years of professional software engineering experience building and operating production backend, platform, data, or distributed systems.
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Strong proficiency in at least one production backend language - Go or Python experience is strongly preferred
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Experience designing distributed services and asynchronous job-processing systems, including concurrency, retries, idempotency, failure recovery, and horizontal scaling
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Experience designing and implementing production APIs using Protobuf/gRPC, including versioning, compatibility, authentication, and authorization
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Strong relational database knowledge, including relational data modeling, schema migrations, referential integrity, query design, indexing, and performance tuning
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Experience with S3-compatible object storage and large analytical, lakehouse, ETL, or time-series data systems
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Experience packaging, deploying, and operating containerized services using Docker, Kubernetes, Helm, and automated CI/CD workflows
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Practical experience with production security and reliability, including IAM, RBAC, secrets management, access controls, audit logging, observability, testing, and incident troubleshooting
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Demonstrated ability to translate architecture and product requirements into incremental implementation plans, production code, and clear technical documentation
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Strong communication and collaboration skills, with the ability to work independently while providing technical leadership and mentorship
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Minimum education requirement - High School Diploma
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Eligible to obtain a U.S. Security Clearance - U.S. Citizenship required
Bonus Qualifications
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Hands-on experience with Apache Iceberg, Parquet, Apache Arrow, or comparable lakehouse and columnar-data technologies
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Experience with distributed queues or workflow orchestration technologies such as Kafka, NATS, RabbitMQ, MQTT, etc...
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Experience with high-throughput data processing technologies such as Spark, Flink, or Beam
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Experience with high volume unstructured telemetry, geospatial data, or other high-rate scientific time-series data
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Experience delivering systems for on-premises, disconnected, or air-gapped production environments/private cloud environments and with infrastructure-as-code practices
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Experience building data platforms that support machine learning training, inference, or model-evaluation workflows
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B.S. or M.S. in an area relevant to this role
Working conditions
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Employees may be called upon to participate in in-person meetings, training, or company functions at Knowmadics offices or other designated locations. Travel in support of business operations may also be required, and employees are expected to comply with these obligations as part of their position.
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Candidate should live within driving distance of the following areas: Round Rock, TX
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Estimated Travel: 0-10%
Physical requirements
May include sitting or standing for extended periods, working with computers and technical equipment, and occasionally lifting or moving materials or tools.
Direct reports
None
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.
