Gen AI Engineer
- Mindlance
1 Days Ago
NA
C2C
Concord-CA
6-10 Years
Required Skills: Python, Microservices, API Development, API Integration, MongoDB, Agentic AI
Job Description
About the Initiative: Part of the Consumer Technology Marketing Technology organization. Focused on building and deploying greenfield Agentic AI solutions. Team is developing AI agents that orchestrate and automate marketing campaign activities. Since launching in March, the team has successfully built 6 AI agents and is now entering the next phase of scaling and enhancement. The first production agents are scheduled to go live on August 24th. Long-term roadmap is expected to expand to 20+ AI agents. This is one of the bank's first major Agentic AI initiatives and is considered a highly visible, strategic program.
Role Overview
Role Overview
- Hands-on development role with a strong coding focus.
- Resources will primarily be building, enhancing, and supporting AI agents rather than spending significant time in meetings.
- Daily collaboration occurs through team standups and close interaction with developers and architects.
- Candidates should be comfortable communicating technical needs and blockers, though executive-facing responsibilities are minimal.
Target Candidate Profile
- Strong backend Python developer with experience building and supporting microservices-based applications.
- Experience designing and consuming APIs.
- Familiarity with Large Language Models (LLMs), Agentic AI frameworks, and AI orchestration concepts.
- Experience working with MongoDB and vector databases.
- Financial services experience is not required.
Required Experience
- Python: 5+ years
- Microservices: 5+ years
- API Development/Integration: 5+ years
- MongoDB: 5+ years
- Agentic AI: 2+ years preferred
Core Technical Skills
- Python software engineering
- REST API development
- Microservices architecture
- Distributed systems design
- Backend service development
- FastAPI
- AsyncIO
- Multiprocessing
- Performance tuning and profiling
- Caching strategies
- Database/query optimization
- Event-driven architecture
- High-availability and fault-tolerant system design
Generative AI / LLM Skills
- Generative AI application development
- Large Language Models
- Agentic AI systems
- Multi-agent workflow design
- Retrieval-Augmented Generation
- Hybrid RAG architectures
- Knowledge graph–enhanced RAG
- Prompt engineering
- Prompt orchestration
- Tool calling
- LLM routing and fallback strategies
- Fine-tuning evaluation
- Model evaluation frameworks
- Hallucination detection
- Human-in-the-loop validation
- Text-to-SQL using LLMs
- Schema-aware prompting
- Embeddings and semantic search
AI Platform & Architecture Skills
- Enterprise AI platform architecture
- Scalable AI workflow design
- AI governance standards
- AI guardrails implementation
- Responsible AI controls
- PII redaction
- Audit logging
- Model usage monitoring
- Latency, cost, and accuracy optimization
- AI/ML feature engineering
- Recommendation systems
- Feedback loops for model improvement
Data Engineering Skills
- Kafka
- Streaming data pipelines
Databases & Vector Search
- Vector database architecture
- Semantic retrieval
- Re-ranking
- Embedding pipelines
