AI Data Engineer
EagleView Technologies View all jobs
- Bangalore, Karnataka
- Permanent
- Full-time
OverviewThe AI Data Engineer will help develop and implement scalable AI and agentic systems for interpreting and exploiting aerial imagery. You’ll help develop end-to-end AI solutions—spanning model pipelines, APIs, and deployment workflows—that interface seamlessly with large imagery datasets and downstream applications. This is a high-impact, cross-functional role requiring hands-on technical skills, strategic thinking, and strong communication. This position will work in parallel with others to advance new ideas as they emerge from Eagleview Innovation Labs and into the hands of customers.We are a fast-paced, energetic team driven by continuous process improvement. We’re looking for motivated, organized, and independent team members. This position requires excellent communication skills and the ability to quickly pick up new technologies.
ResponsibilitiesAI Data Infrastructure & Pipeline Development:
- Develop, and implement AI/ML models and algorithms to solve complex business problems and improve operational efficiency.
- Build and maintain tools, datasets, and data resources optimized for AI systems, including structured datasets, knowledge bases, and data pipelines that support model training and LLM applications.
- Develop and integrate LLM-based solutions using modern GenAI tooling such as prompt engineering, RAG pipelines, and agent frameworks.
- Evaluate and optimize LLM outputs for accuracy, bias, safety, and reliability while ensuring cost-effective usage of AI infrastructure.
- Work with tools and frameworks such as PyTorch, Hugging Face, LangChain, LangGraph, Langfuse, and related AI orchestration
- Collaborate with engineering, product, and data teams to integrate AI solutions into production systems and existing workflows.
- Implement data pipelines to extract insights from large datasets and support AI system development and evaluation.
- Stay current with emerging LLM models, AI tooling, and GenAI trends, and proactively introduce improvements to systems and workflows.
- Ensure responsible AI development by incorporating data privacy, ethical considerations, and governance practices into AI solutions.
- Participate in technical reviews, design discussions, and planning meetings, and clearly communicate technical decisions, risks, and trade-offs.
- 2–4 years of hands-on experience in software engineering, data analysis, or applied machine learning engineering.
- Strong programming experience in Python, with familiarity in Go or TypeScript for building AI-enabled systems or services.
- Practical experience working with LLMs, prompt engineering, RAG architectures, or agent frameworks.
- Familiarity with AI orchestration tools such as LangChain, LangGraph, Langfuse, or similar frameworks.
- Experience working with cloud platforms such as AWS, including services that support AI or data pipelines.
- Strong analytical and problem-solving skills with the ability to work on complex data-driven problems.
- Effective communication skills and the ability to collaborate with cross-functional teams.
- Experience building AI-powered applications using LLM APIs (OpenAI, AWS Bedrock, etc.).
- Knowledge of MLOps / LLMOps, including model deployment, monitoring, and lifecycle management.
- Experience with vector databases, embeddings, and retrieval systems.
- Exposure to multi-agent systems or autonomous workflows.
- Familiarity with data governance, privacy, and responsible AI practices.