ExTrac

Full-stack Engineer

• Build and improve agent loops, including context assembly, tool selection, and sub-agent orchestration
• Build analytical AI features from network construction through analyst-facing summaries
• Run experiments against live analyst traffic behind feature flags
• Define improvement criteria and assess whether approaches should be advanced or discontinued
• Develop approaches for unstructured, imperfect datasets
• Use embeddings for retrieval, network construction, and community detection
• Maintain model-agnostic designs and integrate models and embeddings selected through ML evaluations
• Gather requirements, write technical designs, and ship production features with minimal oversight
• Own services end to end, including consolidation or decommissioning of replaced services
• Design APIs for internal teams and customers with clear contracts and versioning
• Design schemas, indexing strategies, and access patterns across relational, document, and vector stores
• Contribute to and lead system design and architecture decisions
• Design, build, deploy, and operate Python and Go services
• Ensure agent workflows meet production standards for latency, cost, and reliability
• Build and operate long-running streaming pipelines with caching and recovery capabilities
• Work directly with analysts to turn user feedback into system changes
• Iterate on product requests and identify conflicts with longer-term capability work
• Partner with the ML team to productionize agentic approaches and solve engineering, performance, and reliability challenges
• Integrate and serve trained models and build production infrastructure for evaluation frameworks

Senior AI Software Engineer

• Build and improve agent-loop components including context assembly, tool selection, and sub-agent orchestration
• Build analytical AI features from network construction through analyst-facing summaries
• Run experiments against live analyst traffic behind feature flags
• Help define what constitutes an improvement and evaluate evidence
• Use embeddings for retrieval, network construction, and community detection
• Work within a model-agnostic architecture, swapping models and embeddings based on ML evaluations
• Clarify requirements and ship well-defined problems to production
• Own features and components end to end and contribute to system design and architecture
• Build and maintain versioned APIs for internal teams and customers
• Design schemas, indexing strategies, and access patterns across relational, document, and vector stores
• Build and operate supporting Python and Go services
• Improve agent workflows for latency, cost, and reliability
• Build and operate long-running streaming pipelines, including caching and recovery
• Work directly with product analysts to turn practical usage into system changes
• Iterate on product requests while identifying conflicts with longer-term capability work
• Partner with the ML team to productionize agentic approaches
• Integrate and serve trained models and contribute to production infrastructure for evaluation frameworks

AI Software Engineer

• Build and operate backend microservices and pipelines for ExTrac’s decision intelligence platform
• Take ambiguous problems from requirements gathering and technical design through production delivery with minimal oversight
• Own services end to end, including consolidating or decommissioning replaced services
• Contribute to and lead system design and architecture decisions
• Design APIs for internal teams and customers, maintaining clear contracts and versioning
• Design storage schemas, indexing strategies, access patterns, and boundaries
• Develop Go and Python microservices for data collection, processing, and querying
• Maintain production standards for latency, cost, reliability, and instrumentation
• Build and operate high-throughput data streaming pipelines
• Improve scalability, robustness, and latency
• Optimise databases and index performance
• Work directly with analysts to translate product feedback into system changes
• Partner with AI and frontend teams on cross-functional features
• Improve deployment pipelines, service templates, observability, and engineering environments
• Participate in a four-stage interview process: hiring manager interview, technical assessment, competency interview, and founder interview

Senior Backend Software Engineer

• Build and own features, components, and APIs end to end within a single system
• Contribute to system design and architecture discussions
• Build and maintain APIs used by internal teams and customers
• Develop Go and Python-based microservices for data collection, processing, and querying
• Ensure services meet production standards for latency, cost, and reliability
• Build instrumentation to monitor service performance
• Build and operate high-throughput data streaming pipelines
• Improve pipeline scalability, robustness, and latency
• Optimise databases and index performance
• Work directly with analysts to turn practical product feedback into system changes
• Iterate on product requests and identify conflicts with longer-term platform work
• Partner with AI and frontend teams on cross-functional features
• Contribute to deployment pipelines, service templates, observability, and engineering environments

Backend Software Engineer

Machine Learning Engineer

• Contribute to designing systems that balance research velocity with product and production constraints
• Shape technical decisions on model selection, training approaches, evaluation, and deployment for well-defined components
• Build and ship production-ready components combining research rigour with pragmatic engineering
• Take projects from early exploration through to reliable deployment
• Apply high standards for architecture, code quality, evaluation, and research practices
• Work with software engineering and product design to understand requirements
• Contribute to agentic systems for large-scale analysis of the geopolitical landscape
• Train and evaluate domain-specific models
• Translate research into practical solutions for analysts
• Own well-defined components end-to-end and collaborate on broader technical decisions alongside senior engineers
• Participate in an interview process consisting of an initial intro interview, technical assessment, system design assessment, and founder interview

• Partner directly with software engineering and product design to understand requirements
• Design and run model evaluations
• Integrate optimised workflows into production pipelines
• Ensure results remain reliable at scale
• Architect agentic systems for large-scale analysis of the geopolitical landscape
• Train and evaluate domain-specific models for customer problems
• Work with design and engineering to bring models into the product
• Translate research into practical solutions for analysts alongside domain experts
• Lead technical direction on major initiatives
• Set standards across the team and mentor others
• Take projects from prototype through reliable production deployment
• Collaborate with engineers designing the data collection and processing backend
• Engage directly with senior stakeholders
• Make technical decisions on model selection, training approaches, evaluation and deployment
• Deliver production-ready systems at scale
• Uphold standards for architecture, code quality, evaluation and research practice

Senior AI Software Engineer

AI Software Engineer

Senior Backend Software Engineer

Backend Software Engineer

Machine Learning Engineer

Senior Machine Learning Engineer