Dobs.ai

AI Engineer

Experience Level: 3-5+ years of overall engineering experience, including at least 1 year working with LLM-based agentic systems

 

About Us

We’re building a next-generation platform that leverages Large Language Models (LLMs) and agentic workflows to transform document processing, analytics, and decision-making for large interprises (Top Fortune 1000). Our fast-growing team is looking for an AI Engineer who will design and implement robust agent flows, integrate advanced LLM frameworks and design patterns, and optimize context-building from multiple data sources.

 

What You’ll Do

  • Design & Implement Agentic Workflows
    • Build AI “agents” with memory modules, context-building, and tool integration.
    • Develop strategies for connecting diverse data sources (e.g., DB, Vector Stores, other MCPs) into agent pipelines.
  • LLM Integration & Prompt Engineering
    • Craft effective prompts for chain-of-thoughts for domain-specific tasks (extraction, reasoning, summarization, data augmentation) to reduce hallucinations.
    • Evaluate and fine-tune OpenSource LLM like LLaMA models for specific business needs.
  • Architecture & Best Practices
    • Drive architecture design patterns for robust, scalable AI microservices.
    • Apply best practices in software engineering (CI/CD, testing, code reviews).
  • Data Pipelines & Context Handling
    • Build/maintain data workflows for ingesting and storing large volumes of unstructured/structured data.
    • Collaborate with data team to ensure high-quality data is fed into LLM pipelines.
  • Collaborate Across Teams
    • Work with clients, analyst, product, backend, and devops teams to bring agentic solutions into production.
    • Share your expertise in design and optimization of AI-driven applications.

       

Must-Have Experience

3+ years of software engineering experience (Python preferred).

1+ year of direct experience building LLM-based agentic systems (memory, context-building, tool integration).

✅ Proven track record of prompt engineering and reducing hallucinations in LLM tasks.

✅ Experience with advanced retrieval-augmented generation (RAG) methods like vector databases, knowledge graphs, etc.

✅ Experience building scalable backend systems from scratch / 0-1 (not just maintenance).

✅ Strong understanding of design patterns (both traditional architecture and agentic flow).

Hands-on approach - must verify work through unit testing & end-to-end evals.

 

Nice to Have

  • Background in machine learning or data science (training and deploying models at scale).
  • Understanding of domain-specific best practices (security, compliance, large-scale production environments).
  • Familiarity with data pipelines (ingestion, transformation, storage) for unstructured/structured data.
  • Comfortable with version control, CI/CD, testing frameworks, and containerization (e.g., Docker).

 

Key Responsibilities

  1. Agent Development
    • Implement LLM-based agents with memory/context features and external tool integrations (e.g., DB queries, retrieval APIs).
  2. Prompt Engineering
    • Experiment with chain-of-thought prompts, advanced reasoning flows, and consistent context injection.
  3. Systems Architecture
    • Champion proven architecture design patterns for reliability, performance, and scalability.
    • Contribute to the evolution of the overall software stack (Python backend).
  4. Continuous Improvement
    • Drive the iteration of agentic workflows, measure performance, and optimize real-time data pipelines.
  5. LLM & ML Experimentation
    • (Nice to have) Use ML frameworks to develop ensemble or fallback solutions if LLM context is insufficient.
    • Evaluate model performance on internal validation datasets.

       

Why Join Us

  • Impact & Ownership: Be a founding AI engineer spearheading the design of agentic workflows that push the boundaries of LLM usage.
  • Cutting-Edge Tech: Work with the latest LLMs, advanced memory & context frameworks, and best-in-class software stacks.
  • Growth Opportunities: Shape a core AI function in a fast-paced environment; collaborate with top talent across product, engineering, and data.
  • Flexible Culture: We offer remote/hybrid setups with an emphasis on results over hours.

 

Ready to Build the Future of Agentic AI?

🚀 We look forward to hearing from you!

Required languages

English B2 - Upper Intermediate
Python, AI/ML: RAG, Vector DBs, Docker/Kubernetes, CI/CD, AI
Published 24 September
126 views
·
54 applications
82% read
·
50% responded
Last responded 3 weeks ago
To apply for this and other jobs on Djinni login or signup.
Loading...