Deep Sync

Data Engineer

• Design and evolve scalable, secure, and high-performance data architectures supporting large-volume, high-velocity data.
• Establish data engineering standards, design patterns, and best practices.
• Evaluate and recommend tools, frameworks, and technologies for data processing and storage.
• Lead the design, implementation, and maintenance of robust, scalable data pipelines.
• Ensure data quality, validation, lineage, and observability throughout the pipeline lifecycle.
• Implement fault-tolerant and highly available data processing systems.
• Architect and oversee ETL/ELT frameworks transforming raw data into analytical and operational datasets.
• Integrate data from diverse sources including relational databases, APIs, third-party providers, and streaming platforms.
• Collaborate cross-functionally with product managers, analysts, ML engineers, and software teams.

Senior Data Engineer

Engineering Manager

• Build and lead the Agentic Platform team from scratch, serving as the technical visionary and "Head of AI" for the region.
• Architect and develop the core Agentic AI platform, designing autonomous agents that can reason, plan, and execute complex workflows to drive operational excellence.
• Actively code and prototype key components of the system (Python/LLM frameworks), setting the standard for code quality and architectural patterns.
• Collaborate with global executive leadership to define the AI product roadmap, ensuring alignment with Deep Sync’s broader data and identity strategy.
• Recruit, hire, and mentor a high-performing team of AI engineers and data scientists, fostering a culture of innovation, ownership, and technical excellence.
• Drive the integration of Large Language Models (LLMs) and Generative AI technologies into our deterministic identity graph and marketing solutions.

Principal Engineering Manager – Head of AI

AI Engineer

• Design and implement autonomous agents using frameworks like LangChain, LangGraph, or CrewAI that can interact with internal APIs and external tools to solve multi-step problems.
• Build and optimize high-performance Retrieval-Augmented Generation (RAG) pipelines using vector databases (Pinecone/Milvus) to ground LLMs in our deterministic identity data.
• Take AI prototypes and turn them into scalable, fault-tolerant production services using Python, Docker, and Kubernetes on AWS.
• Experiment with prompt engineering, few-shot prompting, and fine-tuning open-source models (Llama 3, Mistral) to balance performance with cost and latency.
• Build evaluation frameworks (Evals) to measure agent reliability, accuracy, and safety, ensuring our agents perform deterministically in a production environment.
• Work closely with the Principal Engineering Manager to define technical standards, code reviews, and architectural patterns for the growing team.

Senior Data Engineer

Principal Engineering Manager – Head of AI

Senior AI Engineer – Agentic Platform