Abode Techzone LLC
Job Title: Lead Developer - GenAI & RAG Systems
Location
: Austin, TX (Hybrid with 3 days onsite) Type
: Contract Only local candidates Job Summary We are seeking a highly skilled
Lead Developer
with strong expertise in
Python
,
Generative AI (LLMs, RAG pipelines, Embeddings)
, and
GCP Cloud Services
. The ideal candidate will have hands-on experience in building
production-grade AI/ML systems with UI integration
, managing secure enterprise deployments, and ensuring scalability and compliance.
Key Responsibilities
Design, build, and deploy
Retrieval-Augmented Generation (RAG)
pipelines for enterprise GenAI solutions Develop scalable
LLM-based applications
using embeddings, vector databases, and prompt engineering best practices Work with
Azure Functions, Azure OpenAI, Azure ML, Cosmos DB, and Blob Storage
for cloud-native implementations Build robust Python microservices for real-time AI inference and data processing Integrate secure authentication mechanisms (SSO, OAuth, JWT) ensuring
security and compliance standards Collaborate with front-end engineers to build interactive
UIs for AI workflows Lead and mentor junior developers in AI/ML engineering best practices Ensure performance, fault tolerance, and observability in deployed applications Required Skills & Experience
8+ years
of experience in software engineering, with at least
3+ years in AI/ML systems Expertise in
Python
and hands-on experience with
RAG pipelines
,
LLMs (GPT, Claude, LLaMA, etc.)
, and
embedding models GCP stack : Vertex AI, Cloud Functions, Firestore, BigQuery Deep understanding of
enterprise integrations
including
SSO
, authentication, data privacy, and compliance Experience with
vector databases
like Pinecone, FAISS, Weaviate, or Azure Cognitive Search Familiarity with
front-end/UI development
frameworks (e.g. React, Streamlit, Flask for dashboards) Proven record of deploying
production-grade AI applications
with UI and backend integration Preferred Skills
Experience with
LangChain
,
LlamaIndex
, or similar GenAI orchestration frameworks Knowledge of
MLOps practices
and tools (e.g., MLflow, Azure DevOps) Familiarity with
CI/CD pipelines
and containerization using Docker & Kubernetes
: Austin, TX (Hybrid with 3 days onsite) Type
: Contract Only local candidates Job Summary We are seeking a highly skilled
Lead Developer
with strong expertise in
Python
,
Generative AI (LLMs, RAG pipelines, Embeddings)
, and
GCP Cloud Services
. The ideal candidate will have hands-on experience in building
production-grade AI/ML systems with UI integration
, managing secure enterprise deployments, and ensuring scalability and compliance.
Key Responsibilities
Design, build, and deploy
Retrieval-Augmented Generation (RAG)
pipelines for enterprise GenAI solutions Develop scalable
LLM-based applications
using embeddings, vector databases, and prompt engineering best practices Work with
Azure Functions, Azure OpenAI, Azure ML, Cosmos DB, and Blob Storage
for cloud-native implementations Build robust Python microservices for real-time AI inference and data processing Integrate secure authentication mechanisms (SSO, OAuth, JWT) ensuring
security and compliance standards Collaborate with front-end engineers to build interactive
UIs for AI workflows Lead and mentor junior developers in AI/ML engineering best practices Ensure performance, fault tolerance, and observability in deployed applications Required Skills & Experience
8+ years
of experience in software engineering, with at least
3+ years in AI/ML systems Expertise in
Python
and hands-on experience with
RAG pipelines
,
LLMs (GPT, Claude, LLaMA, etc.)
, and
embedding models GCP stack : Vertex AI, Cloud Functions, Firestore, BigQuery Deep understanding of
enterprise integrations
including
SSO
, authentication, data privacy, and compliance Experience with
vector databases
like Pinecone, FAISS, Weaviate, or Azure Cognitive Search Familiarity with
front-end/UI development
frameworks (e.g. React, Streamlit, Flask for dashboards) Proven record of deploying
production-grade AI applications
with UI and backend integration Preferred Skills
Experience with
LangChain
,
LlamaIndex
, or similar GenAI orchestration frameworks Knowledge of
MLOps practices
and tools (e.g., MLflow, Azure DevOps) Familiarity with
CI/CD pipelines
and containerization using Docker & Kubernetes