The Role
Design, build, evaluate, and productionize LLM agents and predictive models for automotive retail. Own tool schemas, RAG systems, prompt/version control, agent evaluation, escalation logic, and full model lifecycle (training, deployment, monitoring, retraining). Quantify model impact and ship production-grade systems integrated with dealership services and lakehouse data.
Summary Generated by Built In
This is a remote position.
Join one of the Philippines' fastest-growing tech companies! Open to Philippine-based candidates only.
About Us
Full Scale is a fully remote-first company that helps businesses build dedicated teams of skilled software engineers. We make it easier for growing companies to find, onboard, and retain high-performing software talent.
About the Role
We are looking for a Data Scientist, Agentic AI to build and productionize machine learning models and LLM-powered agents using real-world business data. You’ll work at the intersection of applied data science and agentic AI, building models for forecasting, customer behavior, identity resolution, and other business use cases while designing AI agents that can use tools, make decisions, and know when to escalate to a human.
This is a hands-on role for someone who can take models and AI systems from development to production and build reliable evaluation and monitoring around them.
What You’ll Do
1. Agentic AI
- Design, build, and evaluate LLM agents with tool use and function calling.
- Build agents that can interact with business systems and perform multi-step tasks.
- Design guardrails, confidence thresholds, and escalation logic.
- Build evaluation frameworks, including offline testing, edge cases, A/B testing, and regression testing.
- Develop and maintain RAG systems, including embeddings, vector search, chunking, retrieval tuning, and re-ranking.
- Manage prompt architecture, versioning, and change control.
- Partner on conversational and voice AI experiences, including latency and quality metrics.
2. Data Science & Machine Learning
- Build, validate, and deploy production machine learning models.
- Work on forecasting, customer lifetime value, customer defection, next-service prediction, identity resolution, and demand-related models.
- Own the full ML lifecycle—from feature engineering and training to deployment, monitoring, and retraining.
- Work with Python and modern ML tools against lakehouse/data warehouse environments.
- Monitor models for drift and performance degradation.
3. Business Impact
- Translate business questions into well-defined data science and modeling problems.
- Communicate model results and business impact clearly to technical and non-technical stakeholders.
- Document methodology, assumptions, and limitations.
Requirements
- 4+ years of professional experience applying data science in production.
- Strong Python and SQL skills.
- Hands-on experience building LLM agents with tool use/function calling.
- Experience building and evaluating RAG systems, including embeddings, vector search, chunking, and retrieval evaluation.
- Strong statistical and data science fundamentals.
- Experience deploying machine learning models to production.
- Experience with AWS cloud ML services such as Bedrock, SageMaker, or Lambda.
- Experience working with a lakehouse or data warehouse environment.
- Strong communication skills and ability to work independently.
Nice to Have
- Experience with Databricks, Spark, or Delta Lake.
- Experience with agent frameworks and orchestration patterns.
- Experience with structured outputs/JSON-mode reliability.
- Voice AI or conversational AI experience.
- Experience with time-series forecasting or causal inference.
- Automotive retail, DMS, CRM, or related domain experience.
- Familiarity with AI safety and evaluation practices, including handling PII in prompts and logs.
Benefits
Why join us:
- 100% remote work setup
- Work from anywhere in the Philippines
- High-impact role working with real production AI systems
- Opportunity to build and shape agentic AI solutions, not just prototypes
- Work with a small, senior, and highly autonomous team
- Build AI and ML systems with measurable business impact
Skills Required
- 4+ years applying data science in production with models that made real decisions
- Strong Python and SQL
- Hands-on experience building LLM agents with tool use and function calling
- Practical RAG experience: embeddings, vector search, chunking, retrieval evaluation, re-ranking
- Sound statistical fundamentals and honest handling of uncertainty
- Experience deploying models to production (not handing off notebooks)
- Working comfort with AWS ML tooling (Bedrock, SageMaker, Lambda) and a lakehouse or data warehouse environment
- Write production-grade code others can run and maintain
- Databricks, Spark, and Delta Lake experience
- Experience with agent frameworks, orchestration patterns, and structured output / JSON-mode reliability
- Voice AI or conversational systems experience (Retell, Vapi, or comparable)
- Time-series forecasting and causal inference exposure
- Automotive retail domain knowledge (DMS, CRM, F&I, fixed operations)
- Familiarity with AI safety and evaluation practice, including handling of PII in prompts and logs
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The Company
What We Do
Full Scale is an offshore development company that provides vetted software engineering teams from the Philippines. Founded in 2018, it solves traditional offshoring problems like high turnover and inconsistent quality by employing a full-time employment model and a respect-first culture, helping businesses scale their technical teams with high-quality developers who think like product owners.
