

Jobs via Dice
Hiring! Sr. Python / Gen AI Lead - Onsite in California
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr. Python / Gen AI Lead in San Jose, CA, offering a minimum 12-month contract at an unspecified pay rate. Required skills include Python, Django, and experience with LLMs and AI tooling. Onsite work is mandatory.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
April 28, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
On-site
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
San Jose, CA
-
🧠 - Skills detailed
#Databases #Docker #Django #MongoDB #AWS (Amazon Web Services) #Redis #Cloud #Flask #API (Application Programming Interface) #PostgreSQL #Regression #Langchain #GCP (Google Cloud Platform) #Python #SQL (Structured Query Language) #FastAPI #NoSQL #AI (Artificial Intelligence) #Security #Scala
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, PropelSys Technologies LLC., is seeking the following. Apply via Dice today!
Position#1:-
We are currently hiring for 10 openings for a Sr. Python / Gen AI Lead position based in San Jose, CA. This is a minimum 12-month contract role requiring 5 days onsite. We are open to all experience levels and visa statuses, including H1B C2C for candidates located in the Bay Area.
The ideal candidate must have expertise in Python, Django, APIs (70%), Agents (10%), Vector DBs (10%), and RAG (10%).
Role Overview:
Role: Sr. Python / Gen AI Lead
Location: San Jose, CA (5 Days Onsite)
Type/Duration: Contract Minimum 12 Months
Visa: Open to any visa status (H1B candidates can be considered on C2C; candidates should preferably be based in the Bay Area)
Experience Level: Open to all levels, as we have 10 openings
Interview Process:
Python Coding Test
2 Rounds of Video Interview
At least 1 round will be conducted in person at client office, Santa Clara, CA (for TP1 or TP2)
GenAI Engineers build the core intelligence layer-agents, workflows, prompts, and decision logic-that power enterprise AI applications.
Technology Stack (Priority Order)
• Languages: Python
• Agent & RAG Frameworks: LangChain, LlamaIndex, DSPy
• LLM APIs: Gemini, Bedrock, Vertex AI, Claude
• Vector DBs: Pinecone, Weaviate (Can be any )
• Evaluation: LangSmith, custom eval pipelines
Key Responsibilities
Build multi-step and multi-agent workflows
Implement RAG pipelines and document retrieval strategies
Design prompt templates, system instructions, and guardrails
Integrate agents with tools, APIs, and internal services
Optimize latency, accuracy, and token usage
Create automated LLM evaluation and regression tests
Required Skills
Strong Python development skills
Hands-on experience with LLMs and embeddings
Solid understanding of prompt engineering and hallucination mitigation
Familiarity with cloud AI services
Position#2:-
Job Description: Python Backend Engineer , Location : San Jose (CA)
Interview Process:
Python Coding Test
2 Rounds of Video Interview
At least 1 round will be conducted in person at client office, Santa Clara, CA (for TP1 or TP2)
Role Overview:
We are looking for a Python Backend Engineer to build the backbone of our platform. You will be responsible for creating high-performance APIs, integrating advanced AI agent logic, and ensuring our infrastructure remains rock-solid as we scale. If you enjoy solving complex architectural puzzles and want to work at the intersection of traditional backend engineering and AI
Core Responsibilities
Scalable API Development: Design, build, and maintain robust, high-throughput APIs (FastAPI, Django, or Flask) capable of handling millions of requests.
Agent Logic Integration: Architect the backend systems that power our AI agents, managing long-running tasks, state persistence, and seamless communication between LLMs and our core services.
Authentication & Security: Implement and manage secure identity protocols (OAuth2, JWT, OpenID Connect) to protect user data and internal endpoints.
Routing & Orchestration: Design efficient request routing and service communication patterns using tools like API Gateways, or Service Meshes.
Required Technical Skills
Language: Expert-level proficiency in Python (3.10+ preferred).
Frameworks: Deep experience with FastAPI, Django
AI Tooling: Familiarity with LangChain, LlamaIndex, or similar frameworks for agentic workflows.
Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate).
Infrastructure: Proficiency with Docker, AWS/Google Cloud Platform, and asynchronous task queues
Dice is the leading career destination for tech experts at every stage of their careers. Our client, PropelSys Technologies LLC., is seeking the following. Apply via Dice today!
Position#1:-
We are currently hiring for 10 openings for a Sr. Python / Gen AI Lead position based in San Jose, CA. This is a minimum 12-month contract role requiring 5 days onsite. We are open to all experience levels and visa statuses, including H1B C2C for candidates located in the Bay Area.
The ideal candidate must have expertise in Python, Django, APIs (70%), Agents (10%), Vector DBs (10%), and RAG (10%).
Role Overview:
Role: Sr. Python / Gen AI Lead
Location: San Jose, CA (5 Days Onsite)
Type/Duration: Contract Minimum 12 Months
Visa: Open to any visa status (H1B candidates can be considered on C2C; candidates should preferably be based in the Bay Area)
Experience Level: Open to all levels, as we have 10 openings
Interview Process:
Python Coding Test
2 Rounds of Video Interview
At least 1 round will be conducted in person at client office, Santa Clara, CA (for TP1 or TP2)
GenAI Engineers build the core intelligence layer-agents, workflows, prompts, and decision logic-that power enterprise AI applications.
Technology Stack (Priority Order)
• Languages: Python
• Agent & RAG Frameworks: LangChain, LlamaIndex, DSPy
• LLM APIs: Gemini, Bedrock, Vertex AI, Claude
• Vector DBs: Pinecone, Weaviate (Can be any )
• Evaluation: LangSmith, custom eval pipelines
Key Responsibilities
Build multi-step and multi-agent workflows
Implement RAG pipelines and document retrieval strategies
Design prompt templates, system instructions, and guardrails
Integrate agents with tools, APIs, and internal services
Optimize latency, accuracy, and token usage
Create automated LLM evaluation and regression tests
Required Skills
Strong Python development skills
Hands-on experience with LLMs and embeddings
Solid understanding of prompt engineering and hallucination mitigation
Familiarity with cloud AI services
Position#2:-
Job Description: Python Backend Engineer , Location : San Jose (CA)
Interview Process:
Python Coding Test
2 Rounds of Video Interview
At least 1 round will be conducted in person at client office, Santa Clara, CA (for TP1 or TP2)
Role Overview:
We are looking for a Python Backend Engineer to build the backbone of our platform. You will be responsible for creating high-performance APIs, integrating advanced AI agent logic, and ensuring our infrastructure remains rock-solid as we scale. If you enjoy solving complex architectural puzzles and want to work at the intersection of traditional backend engineering and AI
Core Responsibilities
Scalable API Development: Design, build, and maintain robust, high-throughput APIs (FastAPI, Django, or Flask) capable of handling millions of requests.
Agent Logic Integration: Architect the backend systems that power our AI agents, managing long-running tasks, state persistence, and seamless communication between LLMs and our core services.
Authentication & Security: Implement and manage secure identity protocols (OAuth2, JWT, OpenID Connect) to protect user data and internal endpoints.
Routing & Orchestration: Design efficient request routing and service communication patterns using tools like API Gateways, or Service Meshes.
Required Technical Skills
Language: Expert-level proficiency in Python (3.10+ preferred).
Frameworks: Deep experience with FastAPI, Django
AI Tooling: Familiarity with LangChain, LlamaIndex, or similar frameworks for agentic workflows.
Databases: Strong knowledge of SQL (PostgreSQL) and NoSQL (Redis, MongoDB), plus experience with Vector Databases (Pinecone, Weaviate).
Infrastructure: Proficiency with Docker, AWS/Google Cloud Platform, and asynchronous task queues






