Job Overview
Location
Remote
Job Type
Full-time
Category
Software Engineer
Date Posted
February 26, 2026
Full Job Description
📋 Description
- • Census Labs is seeking a Principal Software Engineer, Applied AI (Technical Lead) to architect, build, and productize cutting-edge AI-enabled capabilities within our cybersecurity engineering solutions. This is a pivotal leadership role focused on delivering production-grade Large Language Model (LLM) AI systems that exhibit predictable behavior, strong performance, robust failure handling, rigorous evaluation, and maintainable architecture. Unlike research-focused positions, this role is deeply embedded in the engineering lifecycle, requiring you to translate complex AI concepts into tangible, deployable products.
- • As a premier engineering services provider, Census Labs operates at the forefront of cybersecurity, specializing in building secure and resilient systems. Our work is research-driven and engineering-focused, enabling us to deliver bespoke development and custom solutions at the intersection of cybersecurity and emerging technologies. We tackle complex product challenges, helping our partners evolve their platforms across critical domains such as secure communications, IoT, AI-powered systems, and enterprise applications. You will be instrumental in shaping the future of these platforms by integrating advanced AI functionalities.
- • Your primary responsibility will be to own the end-to-end engineering of AI application pipelines and reusable accelerators. This includes defining and implementing the reference architecture for LLM AI features, encompassing service boundaries, APIs, data contracts, trust boundaries, and deployment patterns. You will be tasked with transforming prototypes into production-ready services, ensuring clear interfaces, strict type schema discipline, and controlled dependencies. A key aspect of this role involves defining a comprehensive versioning strategy for prompts, tools, policies, and model endpoints, including robust rollback mechanisms to ensure stability and manageability.
- • You will design and implement sophisticated LLM pipelines, enabling natural language to structured queries for database engines with built-in guardrails. This includes leveraging Retrieval-Augmented Generation (RAG) where appropriate, integrating with vector stores, implementing hybrid retrieval strategies, and managing context effectively. A critical focus will be on the safe execution of tools by LLMs, implementing mechanisms for bounded retries, timeouts, sandboxing, rate limits, and strict output schema validation. You will enforce schema-first output (e.g., using Pydantic models and JSON schema) and ensure robust parsing and validation to maintain data integrity and system reliability.
- • Reliability, performance, and observability are paramount for production inference. You will own the non-functional requirements, including latency budgets, throughput targets, resilience strategies, and cost control. This involves implementing established production patterns such as caching, batching, streaming responses, backpressure queues, circuit breakers, idempotency, and graceful degradation to ensure systems operate smoothly under various conditions. Building comprehensive observability is crucial; you will implement structured logs, traces, metrics, and error taxonomies that make failures immediately actionable and facilitate rapid resolution.
- • AI security is a core concern. You will implement essential AI security controls, including prompt injection defenses, strict tool access controls, data minimization principles, and detailed audit logging, all aligned with stringent client requirements. This proactive approach ensures the integrity and security of the AI systems we deploy.
- • Collaboration and delivery are key to our success. You will translate requirements from client stakeholders and internal security and engineering teams into robust AI-enabled solutions and seamless data integrations. You will lead the technical delivery of AI components across diverse client environments, which may include cloud and on-premises deployments, always adhering to strict security, compliance, and operational constraints. Ownership extends to creating essential handover artifacts, such as architecture documentation, runbooks, deployment guides, and support playbooks, ensuring smooth transitions and ongoing operational success.
- • As a technical leader, you will mentor and uplift our engineering teams. You will act as the technical lead for Applied AI delivery, continuously raising the engineering bar, mentoring Data Science and Software Engineers, and driving a culture of high code quality. This includes owning architectural reviews, developing refactoring plans, and prioritizing technical debt reduction efforts specifically related to reliability and delivery efficiency. Your expertise will guide teams through complex architectural trade-offs in ambiguous environments, fostering innovation while maintaining discipline.
- • You will be responsible for documenting solutions thoroughly and actively participating in knowledge transfer sessions with both internal teams and partner organizations, ensuring best practices are shared and adopted widely.
🎯 Requirements
- • Minimum of 6 years of software engineering experience, with a significant portion dedicated to technical leadership on production systems and AI/ML-powered applications.
- • Proven track record of making impactful architecture decisions and successfully driving cross-team execution to deliver complex projects.
- • Strong proficiency in Python engineering, including experience building scalable services, developing robust tooling, and implementing comprehensive testing strategies for maintainable codebases.
- • Demonstrated experience successfully shipping LLM AI-enabled applications into production environments, managing the full lifecycle from development to deployment and operation.
- • Proven ability to build and maintain robust APIs and services, with experience in frameworks like FastAPI or equivalent.
- • Solid understanding and practical experience with production reliability practices, encompassing observability (logging, metrics, tracing), incident response, performance tuning, and scalability strategies.
- • Comfort and experience integrating with big data and analytics platforms.
- • Excellent written and verbal communication skills in English, with the ability to confidently lead technical discussions with both engineers and client stakeholders.
🏖️ Benefits
- • Competitive salary and performance-based bonuses.
- • Comprehensive health, dental, and vision insurance plans.
- • Generous paid time off (PTO) and company holidays.
- • Opportunities for professional development, including training, certifications, and conference attendance.
- • Remote work flexibility, allowing for a healthy work-life balance.
- • Collaborative and innovative work environment with a focus on cutting-edge technology.
Skills & Technologies
Python
FastAPI
Docker
Kubernetes
Senior
Remote
About Census Labs Limited
Census Labs is a cybersecurity company specializing in digital forensics and incident response. They offer services to help organizations investigate and recover from cyberattacks, analyze compromised systems, and provide expert testimony. Their expertise lies in areas such as malware analysis, network forensics, and data recovery. They serve a diverse range of clients, including law enforcement agencies, government bodies, and private sector companies, assisting them in navigating complex digital investigations and strengthening their overall security posture.
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