AI/LLM Applied Engineer
Engineering Python AI/ML Large Language Models (LLM) SQL Machine Learning
Salary
Location
Benefits
13th month salary
Laptop/desktop for works
Other benefits
Work-from-home
Job Overview And Responsibility
We are building data analytics agents that leverage LLMs to help users extract insights from our data platform (Databricks). These agents must go beyond natural-language interfaces—they are expected to reason over data, generate correct queries, interpret results, and deliver actionable insights that business users can trust. This role is responsible for designing systems where LLMs interact safely and reliably with production data, under real-world constraints such as data scale, schema complexity, governance, and performance. Core Responsibilities - Build an agentic analytics platform using LLMs, including multi-step agents, tool orchestration, and reusable agent skills - Design context engineering and memory systems (session and long-term) to support complex, multi-turn analytics workflows - Enable safe, reliable access to Databricks data through validated SQL generation, semantic layers, and governance guardrails - Transform query results into accurate, explainable, decision-ready insights, not just tables or charts. - Implement automated evaluations and agent observability, including tracing, correctness checks, and failure detection
Required Skills and Experience
- 4+ years of professional experience in software engineering, applied ML, or AI engineering - Hands-on experience building LLM-powered or agentic systems in production: langchain, crewAI, agno, … - Strong proficiency in Python, asynchronous programming and backend system design. - Solid understanding of SQL, analytical queries, and data modeling - Experience designing reliable systems with validation, monitoring, and graceful failure handling: opentelemetry, grafana and prometheus stack, … - Strong intuition for LLM failure modes, correctness, and trust in production systems
Why Candidate should apply this position
- Competitive package - Hybrid working model - Macbook Pro provided for work - Bonus: 13th month salary - Weekly learning sessions and offsites - Close-knit small team culture
Preferred skills and experiences
- Experience building agent platforms, including memory, context management, or tool orchestration - Experience with data systems or data platforms (Databricks, Snowflake, BigQuery, Redshift) - Familiarity with semantic layers, metrics stores, or analytics engineering workflows - Experience implementing LLM evaluation frameworks or automated quality checks - Exposure to observability for AI systems (tracing, logging, confidence scoring, grounding) - Background in data engineering, analytics engineering, or BI platforms
Report to
Chief Digital Officer
Interview process
Overview interview -> Technical interview (90mins) -> Fit interview (in English)
