{"id":2579795,"url":"https://alion.io/job/pear-tree-ai-engineer","title":"AI Engineer","company":{"id":709562,"name":"Pear Tree","domain":"pear-tree.com","url":"https://alion.io/company/pear-tree","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":76,"open_postings":123,"ghost_share":0,"stale_share":0.951,"repost_share":0,"time_to_fill_p50_days":25,"computed_at":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["PH"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Function Calling","optional":false},{"name":"Langfuse","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"MLFlow","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"OWASP Top 10","optional":false},{"name":"PHP","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Tool Use","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-10-14T00:00:00Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T20:40:26Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Position : AI Engineer\nSalary : Up to PHP 120,000/month\nWorking Hours & Conditions: Observing AU working hours\nHolidays : Observing AU holidays\nA boutique consulting firm is looking for an AI engineer to build and deploy production-grade AI and machine learning solutions for enterprise clients. You will turn a client's business problem into a system that fits their needs and that their team can run and maintain after the engagement ends. Clients are listed and privately owned Australian businesses in retail, consumer goods, energy and mining. The work covers LLM applications and classical machine learning, and it includes the data pipelines underneath both. You will work directly with the founder and with client teams, across scoping through to\ngo-live and handover.\nRESPONSIBILITIES:\nDesign the solution architecture, choosing between off-the-shelf models, RAG, agents and custom models based on the client's problem and budget.\nIntegrate LLMs into client systems, including prompt design, tool use and agentic workflows.\nTrain, validate and deploy machine learning models for problems such as demand forecasting and anomaly detection.\nAnalyse client data to test whether a use case is feasible, and build the data pipelines that feed models and applications.\nEvaluate and monitor solutions in production for accuracy, drift, latency and cost, and optimise them as issues appear.\nWrite tested, secure code, with guardrails against prompt injection and data leakage.\nWork with client executives, business users and IT teams to turn business problems into technical requirements and give input into the firm's proposals.\nHand over solutions with documentation and training so that client teams can run them\nRequirements\n5+ years of professional software engineering, including at least two years building AI applications that run in production.\nConsulting or professional services experience, delivering to external clients against a fixed scope.\nA bachelor's or master's degree in computer science, engineering, mathematics or physics, or equivalent practical experience.\nAdvanced Python, including testing, packaging and writing code that other engineers can maintain.\nDaily use of AI engineering tools such as Claude Code or Codex, including reviewing, testing and correcting the code they generate.\nHands-on experience integrating LLMs into applications, including RAG, prompt design, tool use and evaluation.\nExperience building agents with the Model Context Protocol (MCP) or agent frameworks.\nExperience training and deploying machine learning models with libraries such as scikit-learn, PyTorch or XGBoost.\nStrong SQL and experience building data pipelines.\nExperience deploying solutions on at least one cloud platform, preferably Azure or AWS, using containers and CI/CD.\nThe ability to explain technical trade-offs to non-technical executives in plain language.\nDESIRED (NOT REQUIRED):\nExperience with data platforms such as Databricks, Snowflake or Microsoft Fabric, and transformation tools such as dbt.\nExperience with LLM evaluation and observability tools, such as MLflow, Langfuse or LangSmith.\nKnowledge of LLM security risks, such as those in the OWASP Top 10 for LLM Applications.\nExperience running training sessions or workshops for technical or business 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