Entry Level AI Architect Jobs
New grad ai architect jobs are open to recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or hands-on internship work can carry more weight than a long resume. Most openings are across Technology & Software, Consulting & Professional Services, and Education, with employers like EY, Qualcomm, and Amazon Web Services hiring at this level now.
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Key Capabilities:
Agentic AI Architecture:
Solid understanding of Large Language Model (LLM) orchestration, prompt engineering, context windows, and token conservation
Experience designing autonomous routing systems that leverage semantic understanding to execute multi-step tool calls
Enterprise Integration:
Proven expertise in high-scale data synchronization patterns
Masterful command of REST, gRPC, and event-driven architectures (e.g., Salesforce Pub/Sub API) to coordinate distributed cloud systems
Salesforce Customization:
Deep familiarity with wrapping complex backend processes into agentic tools via:
Invocable Apex methods
Advanced Salesforce Flows
Custom prompt templates
Architectural Governance:
Experience authoring comprehensive Architectural Decision Records (ADRs) that clearly map High-Level Requirements (HLRs) against technical constraints and explicit trade-offs
Must-Have Skills (Additional):
Strong experience with enterprise integrations and system architecture
Strong Apex methods, advanced Salesforce Flows, and custom prompt templates
Experience with APIs (REST, gRPC, event-driven architectures)
Experience integrating systems with Salesforce
Knowledge of AI/LLM concepts such as:
Prompt engineering
Context management
Multi-step AI workflows
Agent orchestration
Experience designing scalable and secure distributed systems
Experience with Salesforce tools such as:
Salesforce Flows
APIs and connectors
Understanding of security, authentication, and data governance
Experience documenting architecture decisions and technical trade-offs
Strong collaboration skills across engineering, data, and security teams
Nice-to-Have (Preferred):
Experience with Model Context Protocol (MCP)
Experience with Agent-to-Agent (A2A) integrations
Experience with MuleSoft or middleware platforms
Experience building or managing autonomous AI agents or micro-agent systems
Familiarity with Salesforce Agentforce
Experience with semantic tool discovery or AI-native integrations
Knowledge of Bulk APIs and Salesforce Connect
Experience working in large-scale enterprise AI environments
Role Overview:
Indeed’s GTM Core team is seeking a highly skilled and strategic AI Platform Integration Architect to drive the next generation of our enterprise automation ecosystem. In this role, you will bridge the gap between our internal data architectures and Salesforce’s advanced agentic capabilities. A core focus of this position is the evolution and enterprise scaling of an autonomous AI co-worker built and operated internally.
Key Responsibilities:
System Orchestration & Blueprinting:
Architect end-to-end integration designs connecting Indeed’s internal AI co-worker and related data platform services to Salesforce Agentforce environments
Pattern Optimization & Decisioning
rigorous architectural frameworks to choose the correct integration pattern (Traditional APIs, Model Context Protocol, or Agent-to-Agent) based on:
Transaction volume
Reasoning overhead
Latency boundaries
Data sensitivity
Agent Specialization Management
Design modular agent structures to avoid monolithic, overloaded reasoning engines
Enforce governance limits (e.g., maintaining under 10 topics per agent) by delegating complex tasks across specialized autonomous micro-agents
Cross-Functional Collaboration:
Work directly with Data Engineers, Salesforce Administrators, Core Platform Architects, and Security Operations
Maintain unified API contracts and clean semantic understanding across all endpoints
Security and Trust Governance:
Establish explicit trust filters, secure authentication boundaries, and data exposure guardrails
Protect sensitive corporate assets while maintaining fluid agent execution
The pay range that the employer in good faith reasonably expects to pay for this position is $62.41/hour - $97.52/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.
Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.
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Find Entry Level AI Architect JobsEntry Level AI Architect Job Market
Who's Hiring
- EY4
- Qualcomm4
- Amazon Web Services3
- Tata Consultancy Services (TCS)3
- Photon2

Top Industries Hiring
- Technology & Software15
- Consulting & Professional Services7
- Education5
- Accounting & Auditing5
- Insurance4
Entry Level AI Architect Jobs: Frequently Asked Questions
How do I get an entry level ai architect job?
Focus on building a portfolio that shows real projects: model pipelines, system design documents, or deployed prototypes give hiring managers something concrete to evaluate. Familiarity with cloud platforms, Python, and machine learning frameworks matters at this stage. Internship experience is a strong signal, but self-taught candidates who can demonstrate applied work in AI systems design are competitive for junior and new grad openings.
Which companies hire entry level ai architects?
Companies hiring entry level ai architects right now include EY, Qualcomm, and Amazon Web Services, based on current listings on Migrate Mate as of July 2026. Hiring at this level comes from a wide range of organizations, including enterprise technology firms, AI-focused startups, and large corporations building out internal AI infrastructure.
Are there remote entry level ai architect jobs?
Yes, though availability varies by employer and team structure. About 29% of entry level ai architect openings are remote or hybrid as of July 2026, so there are genuine options for candidates who need location flexibility. Many companies at this level prefer hybrid arrangements so junior hires can work closely with senior architects during the early stages of their career.
Are these new grad ai architect jobs?
Yes, the listings here include new grad, recent graduate, and junior ai architect roles alongside other entry level positions. A posting is typically new-grad friendly when it welcomes zero to two years of experience, accepts internships or academic projects as qualifying background, or explicitly invites candidates with a strong portfolio in place of a long work history. Look for language like "new grad" or "junior" in the job description.
Which industries hire the most entry level ai architects?
Entry Level ai architect roles concentrate in Technology & Software, Consulting & Professional Services, and Education, based on current listings on Migrate Mate as of July 2026. These sectors are actively building or expanding AI infrastructure, which creates consistent demand for junior talent who can contribute to architecture design, model deployment, and system integration from an early career stage.