{"id":2833730,"url":"https://alion.io/job/lhasa-limited-principal-ai-engineer","title":"Principal AI Engineer","company":{"id":2398211,"name":"Lhasa Limited","domain":"lhasalimited.org","url":"https://alion.io/company/lhasalimited","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"B","score":75,"open_postings":3,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-22T06:10:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Bitbucket","optional":false},{"name":"CI/CD","optional":false},{"name":"Context Engineering","optional":false},{"name":"Docker","optional":false},{"name":"Hallucination","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Java","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Node JS","optional":false},{"name":"Python","optional":false},{"name":"TypeScript","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-07-23T00:00:00Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-22T16:43:16Z","board_verified":true,"closed_at":null,"days_open":91,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":91},"description":"Principal AI Engineer (Brazil based)\nCompetitive, depending on experience\n\nPermanent, Full Time\n\nBrazil (Remote)\n\nSalary\nCompetitive, depending on experience\nLocation\nBrazil (remote)\nSummary of the role\nThe Principal AI Engineer provides strategic AI-first engineering leadership for Lhasa Software Development at portfolio level. As the technical lead of a solutions team, they own engineering standards, AI governance, and AI-human collaboration patterns across Lhasa, and design and govern the multi-agent workflows that deliver consistent, high-quality software at scale. The Principal AI Engineer sets the standard for how AI becomes the primary mechanism for achieving them, with human engineering judgement and authorship applied where the work demands it.\nThe Principal AI Engineer sets the standard for AI-first software engineering across the function, brings deep engineering judgement across architecture, distributed systems, performance, and security, mentors the wider Software Development team, and contributes to the technical roadmap and enterprise AI strategy.\nMain Responsibilities\nAI-First Software Engineering\nSet the architectural guardrails, technical standards, AI harness patterns, and acceptance frameworks for AI agents portfolio-wide\nDesign and govern multi-agent workflows where specialist AI agents handle design, implementation, and testing under appropriate human oversight; define requirements, acceptance criteria, and quality gates\nOwn the design and governance of automated security and quality gates in the development pipeline; ensure security-by-design and quality-by-design are embedded from the point of AI code generation\nValidate AI-generated code, architecture, and tests at portfolio level; intervene directly on complex business logic, distributed-system concerns, performance, and security\nManage AI reliability and hallucination risks at scale; design appropriate human-in-the-loop checkpoints for situations where AI delivery alone is insufficient\nDirect AI coding agents and harnesses to design, implement, test, and support software across the Life Sciences domain; apply deep domain knowledge to validate the result\nCarry out hand-written code, debugging, and design work where AI tooling is unlikely to produce the right result, or where the engineering risk warrants direct human authorship\nEmbed engineering quality early and continuously across multiple products\nTake ownership of complex engineering problems across the portfolio and ensure they are successfully resolved\nStrategy and Engineering Architecture\nLead Technical Excellence strategy, continuous improvement, and outcomes across Lhasa Software Development\nEnsure that software products satisfy architectural characteristics including performance, data confidentiality, resilience, scalability, and security across the portfolio\nDefine decision criteria and technical constraints; use AI-generated evidence to inform strategic technical decisions in collaboration with Product Owners, Delivery Managers, and other Principal Engineers\nMaintain a deep understanding of AI capabilities and limitations; design AI-human collaboration models that balance automation with human judgement at portfolio scale\nDefine AI agent capability requirements and orchestration frameworks; own the technical roadmap contribution for Software Development; collaborate on enterprise AI governance\nOwn context engineering standards, AI harnesses, and governance across Lhasa; ensure engineering knowledge is embedded in agent infrastructure and not dependent on any single individual\nProvide expert technical input to portfolio-level AI compute cost decisions in collaboration with Engineering Management\nProduce architectural design documentation for product solutions; lead the development and iteration of engineering standards in collaboration with senior colleagues\nTechnical Leadership\nServe as the technical lead for a solutions team, providing direction, setting standards, and being accountable for technical outcomes across the portfolio\nDevelop the engineering capability of the Software Development function for AI agent orchestration; build AI-human collaboration skills across teams; focus mentorship on outcome definition, engineering judgement, and AI-limitation awareness\nPioneer and champion best practices observed within Lhasa and externally; raise the engineering bar across the function\nIdentify engineering gaps across the portfolio and own the plans to address them\nCollaborate with the Architecture Team and contribute to product and portfolio architecture\nTechnically lead the software engineering discipline within Lhasa alongside other Technical Leaders\nCommunication and Collaboration\nCommunicate clearly with delivery teams and senior stakeholders; keep all parties informed of technical progress, risks, and decisions at portfolio level\nCascade technical strategy and engineering standards across Software Development; ensure alignment between technical direction and business goals\nRepresent Software Development across Lhasa and with senior stakeholders where required\nAct as a key technical contact for all delivery team members, including those external to Software Development\nActively contribute to the Software Development community of practice\nCulture and Continuous Improvement\nLead by example as the role model for AI-first software engineering across the function; champion Lhasa’s values\nDesign innovative AI-human collaboration models; identify opportunities for expanded AI capability; keep current with advances in AI technologies and orchestration\nBe accountable for the technical excellence of solutions from design through to production operations\nLive the cultural values of Ownership, Integrity, Collaboration, Diversity & Inclusivity, and Curiosity & Adaptability\nUndertake additional tasks and responsibilities which may be reasonably expected of the role\nPromote the visibility of Lhasa within professional networks and at external events\nAdditional responsibilities\nThe following responsibilities may apply based on business need and individuals’ aspirations, skills, and suitability:\nPeople leadership responsibilities may apply based on business need and individual aspiration.\nUndertaking additional tasks to achieve the outcomes of the Software Development function may apply based on business need.\nAbout You\nAI-first, engineering-minded, and strategic. Collaborative, professional, and supportive. Takes full accountability for technical outcomes at portfolio scale, thinks beyond the immediate task to the broader technical and business outcome, and continuously seeks better ways to use AI to accelerate and improve delivery. Models openness to change at a strategic level and shapes engineering culture across Software Development. Conscientious with strong attention to detail and committed to continuous professional development in a rapidly evolving field.\nEducation and Qualifications\nEssential\nDegree level or equivalent in Computer Science, Mathematics, Chemistry, or a related discipline\nExceptional commercial track record of leading technical delivery at system or portfolio level in lieu of degree\nSkills, Knowledge and Experience\nEssential\nProven ability to design AI agent orchestration workflows, AI harnesses, and validate AI-generated architectural designs at portfolio level\nDeep expertise in AI agent orchestration platforms, multi-agent system architecture, context engineering, AI harnesses, and the capabilities and limitations of AI\nDeep and extensive commercial experience in software engineering, with a proven track record of technical leadership and strategic influence\nStrong knowledge of software architecture patterns and systems thinking at portfolio level\nPractical experience designing, writing, debugging, and maintaining production code, the craft that underpins effective AI direction and validation\nExperience of designing and delivering distributed systems or enterprise-scale applications\nExperience of non-functional engineering at enterprise scale including performance, security, resilience, and scalability, and an ability to balance these against delivery pressure\nExperience designing AI-augmented Agile delivery workflows and AI governance frameworks\nExperience with at least one modern backend language (e.g. Java, Python, TypeScript/Node.js), cloud platform (e.g. AWS), CI/CD tooling (e.g. Jenkins, Bitbucket Pipelines), and containerisation (e.g. Docker, Kubernetes); breadth across the stack matters more than depth in any single tool\nWorking knowledge of AI coding assistants, AI code-review tooling, and multi-agent orchestration frameworks; keeping current with this fast-evolving landscape is expected\nExperience of quality gates for AI-generated code and automated validation tooling at portfolio level\nExperience of acting as a technical lead of a solutions team\nDesirable\nExperience with microservices, multithreading, and performance profiling\nExperience of developing software products in a scientific domain\nExperience of performance and line management in a matrix environment\nInterested? Apply now\n\"*\" indicates required fields\nEqual opportunities statement\nLhasa Limited aims to ensure that no job applicant, colleague, or worker receives less favourable treatment on the grounds of race, colour, caste, national or ethnic origins, sex, pregnancy or pregnancy related reasons, marital or civil partnership status, sexual orientation, disability, membership or non-membership of trade union, “spent convictions” of ex-offenders, class, age, political or religious belief.\nLhasa will make reasonable adjustments for all candidates who have declared that they have a disability at all stages in the recruitment process. 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