# Incedo Inc. — Agentic AI Lead

- Generated: 2026-09-24 02:14:43 PM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4471623475/
- Provider: LinkedIn
- Posting time: 1 hour ago
- Applicants: Be among the first 25 applicants
- Work model/location: On-site/location-specific — San Diego, California; Austin, Texas; or Fort Mill, South Carolina
- Compensation: Not disclosed; the title is outside Keith's missing-compensation exception
- Travel: Not disclosed
- Positioning track: Technical IC
- Fit outcome: FAIL — 96%

## Evidence map and direct-match strengths

- Near-direct technical match for production-grade agentic platforms, Python, AWS, Bedrock, SageMaker, RAG, multi-agent orchestration, LangGraph/LangChain, vector databases, governance, observability, and technical-team leadership.

## Hard or material gaps

Independent hard conflicts: the posting specifies three non-Massachusetts locations without remote eligibility, and no compensation is disclosed for a Lead title outside Keith's exception.

## Full normalized job description

Job Title:
Agentic AI Lead / Architect
Location:
San Diego, CA / Austin, TX / Fort Mill, SC
Employment Type:
Full-time
Job Overview
We are seeking an experienced
Agentic AI Lead / Architect
to drive the design, development, and deployment of next-generation AI solutions. The ideal candidate will have hands-on experience building and scaling at least one
production-grade Agentic AI platform
, strong expertise in
Python and AWS
, and the ability to engage directly with clients while leading technical teams. This role will be responsible for architecting intelligent agent ecosystems, defining AI strategy, and delivering enterprise-scale AI solutions.
Key Responsibilities
Lead the architecture, design, and implementation of enterprise-grade Agentic AI platforms and applications.
Build and deploy autonomous AI agents leveraging LLMs, RAG, multi-agent orchestration frameworks, and workflow automation.
Design scalable, secure, and highly available AI solutions on AWS cloud services.
Collaborate with business stakeholders, clients, product teams, and engineering teams to translate business requirements into AI-driven solutions.
Define architecture patterns, best practices, governance, monitoring, and AI observability standards.
Drive technical decision-making across AI/ML, cloud infrastructure, vector databases, and agent frameworks.
Mentor and guide engineering teams through solution design, development, deployment, and optimization.
Lead client discussions, technical workshops, architecture reviews, and executive presentations.
Ensure AI solutions meet enterprise standards for security, compliance, scalability, and performance.
Stay current with emerging trends in Generative AI, Agentic AI, LLMs, and cloud-native architectures.
Required Qualifications
10+ years of overall software engineering experience with at least 3+ years in AI/ML or Generative AI solution architecture.
Strong proficiency in
Python
with experience building scalable AI applications.
Deep expertise in
AWS
services including Lambda, ECS/EKS, Bedrock, SageMaker, API Gateway, DynamoDB, S3, CloudWatch, and related cloud-native services.
Proven experience designing and delivering
at least one production-grade Agentic AI platform
in an enterprise environment.
Hands-on experience with:
Large Language Models (OpenAI, Claude, Llama, Bedrock Models, etc.)
Agentic AI frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel, LangChain)
RAG architectures and vector databases
Prompt engineering, AI evaluation, and observability
API design and microservices architecture
Strong knowledge of software architecture, distributed systems, and scalable application design.
Experience leading technical teams and driving architecture governance.
Excellent communication, stakeholder management, and client-facing presentation skills.
Preferred Qualifications
Experience in
Financial Services, Capital Markets, Banking, Trading, or Investment Management
domains.
Exposure to trading systems, market data platforms, risk management, or financial analytics.
Experience implementing AI governance, security, and responsible AI practices.
AWS Solutions Architect, Machine Learning, or AI-related certifications.
Key Skills
Agentic AI Architecture
Multi-Agent Systems
Generative AI & LLMs
Python
AWS Cloud
LangGraph / CrewAI / AutoGen
RAG & Vector Databases
AI Observability & Evaluation
Microservices & APIs
Solution Architecture
Stakeholder & Client Management
Team Leadership