{"id":3620555,"url":"https://alion.io/job/enumerate-tech-lead","title":"Tech Lead","company":{"id":14568,"name":"Enumerate","domain":"goenumerate.com","url":"https://alion.io/company/enumerate","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"Leadership","role_family":"Leadership","seniority":"lead","employment_type":null,"work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["AR","BR","CO","MX","AI","AG","AW","BS","BB","BZ","BM","BO","VG","BQ","KY","CL","CR","CW","DM","DO","EC","SV","FK","GF","GD","GP","GT","GY","HT","HN","JM","MQ","MS","NI","PA","PY","PE","PR","KN","LC"],"hiring_countries_total":48,"salary":{"min":3500,"max":4500,"currency":"USD","period":"month","gross":null,"usd_annual":54000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"GCP","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Node JS","optional":false},{"name":"Python","optional":false},{"name":"Agile","optional":true},{"name":"JavaScript","optional":true},{"name":"LLM","optional":true},{"name":"Prompt Engineering","optional":true}],"status":"live","first_seen_at":"2026-11-02T15:00:34Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-04T13:06:10Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"The Tech Lead is responsible for translating product ideas and data science capabilities into production-ready AI solutions. This role partners closely with Product Management and the Data Science Leader to rapidly design, prototype, and ship AI-driven features that deliver measurable business value.This is a highly hands-on technical leadership role focused on speed, pragmatism, and production quality, balancing experimentation with scalable engineering practices. \n This is a remote opportunity. We are seeking contractors located in LATAM who are comfortable working in an English-speaking professional environment.\nKey Responsibilities \nAI Solution Delivery & Architecture \nLead the technical design and implementation of AI-powered product features from concept through production. \nOwn end-to-end architecture for AI solutions, including data flows, model integration, APIs, and application integration. \nMake pragmatic decisions to accelerate delivery while maintaining system integrity. \nEnsure AI solutions are secure, observable, scalable, and aligned with platform standards. \nPod Leadership & Execution \nAct as the technical lead for a cross-functional AI Pod. \nBreak down product requirements into executable technical workstreams and prototypes. \nGuide rapid iteration cycles, proofs-of-concept, and MVPs, balancing experimentation with production readiness. \nReview code, architecture, and technical decisions to maintain quality and velocity. \nProduct & Data Collaboration \nPartner closely with Product Management to shape problem definitions, success metrics, and delivery plans. \nCollaborate with the Data Science Leader to integrate models, analytics, and data assets into product workflows. \nTranslate data science outputs into consumable APIs, services, and product features. \nProvide technical feedback on feasibility, scope, and tradeoffs during product discovery. \nOperationalization & Quality \nEnsure features are production-grade, including monitoring, logging, and performance tracking. \nImplement guardrails around AI usage, including reliability, latency, cost controls, and failure modes. \nSupport experimentation frameworks, A/B testing, and post-launch learning loops. \nDrive responsible AI practices, including explainability, bias awareness, and data privacy considerations. \nTechnical Standards & Enablement \nDefine and enforce lightweight engineering standards for AI-enabled systems. \nPromote reuse of components, prompts, pipelines, and services across AI initiatives. \nMentor pod engineers on AI-adjacent system design and best practices. \nContribute to internal documentation and shared AI patterns/playbooks. \nRequired Qualifications \nBS or MS in Computer Science, Engineering, or related technical field. \n5+ years of software engineering experience, including leading complex systems. \nStrong experience designing and building production APIs and backend services. \nProficiency in Python and at least one backend language (e.g., Java, Node.js, Go). \nExperience with cloud-native architectures (AWS, GCP, or Azure). \nSolid understanding of data pipelines, model serving, and system observability. \nAbility to work closely with product teams in fast-moving, iterative environments. \nPreferred Qualifications \nExperience working in AI-first or data-driven product teams. \nFamiliarity with modern LLM platforms, prompt engineering, and agent frameworks. \nExperience operationalizing ML models (model 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