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DTN

Real-time data and analytics for agriculture

Lead Platform Engineer

Platform EngineeringUpdated on Nov 12
Full-timeDallas, TX, USA

About the Job

Requirements

  • 7+ years of professional software engineering experience building and operating production distributed systems.
  • Demonstrated ability to own complex software components and systems throughout their lifecycle.
  • Ability to lead technical initiatives, establish engineering direction, and make architectural decisions.
  • Experience mentoring engineers through technical design guidance, code reviews, and collaborative development.
  • Bachelor's degree in Computer Science or equivalent professional experience.
  • Deep expertise in AWS cloud-native architecture, including identity and access management, serverless compute, API layers, managed data stores, event-driven services, and cloud security primitives.
  • Strong understanding of distributed-systems fundamentals, including idempotency, at-least-once delivery, eventual consistency, retries, backoff strategies, and failure-mode analysis.
  • Experience designing, developing, and operating secure, reliable, and scalable distributed applications.
  • Hands-on experience with infrastructure as code using Terraform.
  • Strong software build, testing, and deployment discipline, including continuous integration and automated testing.
  • Applied security engineering experience involving authenticated service-to-service communication, including technologies such as mutual TLS.
  • Experience with cryptographic signing and verification, identity management, replay protection, and least-privilege access design.
  • Ability to reason through complex security requirements, distributed-system failure scenarios, and multi-tenant isolation risks.
  • Proficiency in TypeScript/Node.js or ability to become productive with these technologies quickly.
  • Academic or professional software development exposure to front-end technologies such as React, Angular, or Vue.
  • Academic or professional software development exposure to back-end technologies such as Node.js or Python.
  • Academic or professional experience with SQL and database technologies such as PostgreSQL, DynamoDB, or equivalent platforms.
  • Expert-level experience developing APIs using RESTful services built with Node.js.
  • Expert-level experience consuming REST and GraphQL APIs.
  • Journeyman-level knowledge of source control and versioning using Git.
  • Hands-on experience using modern AI-assisted development tools, including coding assistants and agentic tooling, to improve engineering productivity.
  • Hands-on experience designing and building AI-augmented platform capabilities, including large language model and AI-agent integrations and managed AI services.
  • Ability to incorporate AI-enabled functionality into modular, reusable platform components.
  • Strong technical problem-solving skills and ability to evaluate complex architectural alternatives.
  • Ability to independently guide complex engineering work from design through production operation.
  • Demonstrated ability to communicate technical direction, provide constructive engineering feedback, and mentor engineers.
  • Commitment to building secure, reliable, observable, and reusable engineering solutions.

Responsibilities

  • Lead the technical design, implementation, delivery, operation, and ongoing evolution of complex platform capabilities.
  • Define engineering problems, evaluate architectural alternatives and technical tradeoffs, and propose scalable, secure, and maintainable solutions.
  • Partner with Enterprise Architecture to design and implement foundational platform capabilities.
  • Own complex components end-to-end, from developer-facing interfaces through the underlying cross-account cloud infrastructure.
  • Design, develop, and maintain developer-facing APIs, software development kits, command-line interfaces, module frameworks, and managed platform services.
  • Build reusable abstractions and platform capabilities that let engineering teams develop data products, applications, and AI-powered solutions without directly managing cloud infrastructure.
  • Lead development of greenfield platform capabilities while maintaining and evolving existing systems.
  • Establish architectural patterns and technical approaches that support scalability, reliability, security, and developer productivity.
  • Design and build secure distributed systems that operate reliably across isolated AWS accounts and multi-tenant environments.
  • Develop secure cross-account communication mechanisms and infrastructure supporting multi-tenant isolation.
  • Design and implement provisioning and lifecycle automation for cloud-based platform capabilities.
  • Build asynchronous and event-driven processing capabilities, including reliable message handling, retries, backoff strategies, and idempotent operations.
  • Develop service discovery, reconciliation, and health-monitoring capabilities for reliable platform operations.
  • Apply distributed-systems principles, including at-least-once delivery, eventual consistency, failure-mode analysis, and resilient service interactions.
  • Evaluate communication failures, service interruptions, and isolation-boundary violations and design safeguards.
  • Develop cloud-native solutions using AWS identity and access management, serverless compute, API services, managed data stores, event-driven services, and cloud security primitives.
  • Build and maintain infrastructure using Terraform and infrastructure-as-code practices.
  • Own the design and implementation of security-critical platform components and communication paths.
  • Design and harden authenticated service-to-service communication mechanisms, including mutual TLS.
  • Implement cryptographic signing, signature verification, and replay-protection mechanisms.
  • Design and maintain secure identity and access management patterns across cloud accounts and services.
  • Apply least-privilege access principles and secure multi-tenant isolation practices.
  • Analyze security-related failure modes and potential isolation breaches to strengthen platform resilience.
  • Integrate security requirements into platform architecture, interfaces, infrastructure, and operational practices.
  • Lead development and evolution of platform SDKs, APIs, CLIs, and shared module framework.
  • Design reusable capabilities that let engineering teams focus on business logic while the platform manages common technical requirements.
  • Define and implement interface contracts, data contracts, and consistent integration patterns.
  • Develop framework functionality supporting authentication, authenticated dispatch, validation, metrics, retries, and reconciliation.
  • Translate repeated engineering requirements into reusable, standardized platform components.
  • Design developer-facing interfaces that promote consistency, maintainability, and productive integration across engineering teams.
  • Support schema-driven interface definitions and validation to improve reliability and interoperability.
  • Establish and guide the team's technical direction, architectural standards, and engineering best practices.
  • Author and review technical designs and architecture decision records to document engineering decisions and tradeoffs.
  • Define and maintain interface standards, data contracts, testing expectations, infrastructure-as-code practices, and observability requirements.
  • Provide technical leadership through architecture discussions, design reviews, code reviews, and collaborative problem-solving.
  • Mentor mid-level and earlier-career engineers through technical feedback, pairing, and hands-on guidance.
  • Improve engineering quality and team effectiveness by sharing expertise, improving development practices, and helping others build technical judgment.
  • Contribute to continuous improvement of engineering processes, development standards, and platform architecture.
  • Own operational reliability and production health of assigned platform components and services.
  • Instrument platform services with metrics, logging, tracing, and observability capabilities.
  • Define and support service-level objectives and operational reliability expectations.
  • Participate in on-call rotations and investigate production incidents involving distributed systems, cross-account interactions, and cloud infrastructure.
  • Troubleshoot complex failures and implement improvements that reduce recurring incidents and operational toil.
  • Maintain build, test, and deployment discipline through continuous integration, automated testing, and reliable release practices.
  • Apply trunk-based development, infrastructure as code, immutable and pinned releases, least-privilege access, and schema-validated interfaces.
  • Continuously improve system resilience, debuggability, operational efficiency, and production stability.
  • Use modern AI-assisted software development tools, including coding assistants and agentic development technologies, to improve engineering effectiveness.
  • Apply AI development tools to accelerate software development, technical problem-solving, and engineering productivity.
  • Design and build AI-augmented capabilities within modular platform components.
  • Integrate large language models, AI agents, and managed AI services into platform capabilities.
  • Evaluate and implement AI-related technologies that expand the functionality and value of the Operational Decisioning Platform.

Desired Qualifications

  • Experience building multi-tenant SaaS platforms, cross-account control planes, or internal developer platforms and SDKs.
  • Experience designing APIs and SDKs consumed by other engineers, with attention to developer ergonomics, consistency, and usability.
  • Familiarity with observability technologies such as OpenTelemetry.
  • Experience with schema-driven interface validation.
  • Awareness of multi-cloud architectures and technologies.
  • Experience developing platform components using TypeScript/Node.js, Python, containers, Terraform, and modern AWS cloud-native services.
  • Experience building secure cross-account infrastructure and developer-facing abstractions in greenfield platform environments.
  • Familiarity with module frameworks that manage authenticated dispatch, signing, validation, metrics, and reconciliation.
  • Experience applying trunk-based development, architecture-decision-record-driven design, immutable or pinned releases, least-privilege access, and schema-validated interfaces.
  • Background in operational or data-intensive industries such as energy, logistics, weather, or agriculture.

About the Company

DTN

Real-time data and analytics for agriculture

DTN provides subscription-based data and analytics for industries sensitive to weather and markets, including agriculture, energy, and broader finance. Its product is an advanced operational decisioning platform that delivers real-time insights by aggregating weather data, commodity prices, and market analytics through a unified system. Historically rooted in delivering real-time price and weather information via radio and satellite, DTN expanded through strategic acquisitions to offer a broad suite of data feeds and analytics that help customers manage risk and seize opportunities. Unlike many competitors, DTN combines weather prediction, commodity and energy market data, and decisioning tools within one platform, backed by decades of industry experience and a track record of growth through acquisitions. The company's goal is to provide timely, actionable information that lets businesses anticipate changes, manage risk, and optimize operations.

Company size
1,001-5,000
Company stage
Grant
Total funding
$1.2M
Headquarters
Bloomington, IN
Founded
1984

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