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Entry Level Ai Agent Developer Jobs (NOW HIRING)

Tata Consultancy Service Limited

AI Developer

Cincinnati, OH · On-site

$100K - $150K/yr

Must Have Technical/Functional Skills AI Developer, Test support, Strong documentation and problem ... Technical Design Agents Configuration (Config) Agent AI Testing and Quality-focused agents Support ...

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Entry Level Ai Agent Developer information

What is an entry level AI agent developer?

Entry Level AI Agent Developers are professionals who assist in designing, building, and maintaining artificial intelligence agents, such as chatbots or virtual assistants, often under the supervision of more experienced engineers. They typically work with programming languages like Python and use machine learning frameworks to help create intelligent systems that can interact with users or perform tasks autonomously. These roles are suited for those new to the field and often require a foundational understanding of AI concepts, basic coding skills, and a willingness to learn advanced topics on the job.

What are the key skills and qualifications needed to thrive as an entry level AI agent developer?

To thrive as an Entry Level AI Agent Developer, you need a solid understanding of programming languages (such as Python), basic machine learning concepts, and a relevant degree in computer science or a related field. Familiarity with AI frameworks (like TensorFlow or PyTorch), API integration, and version control systems (e.g., Git) is typically required. Problem-solving ability, eagerness to learn, and effective teamwork are standout soft skills for this role. These skills and qualities are vital for building, maintaining, and improving AI agents in a collaborative and rapidly evolving tech environment.

What does an entry level AI agent developer do?

As an Entry Level AI Agent Developer, you can expect to work on tasks such as building and fine-tuning conversational AI agents, assisting with data preprocessing, and implementing basic machine learning models under the guidance of senior engineers. You’ll likely contribute to updating or troubleshooting existing AI agents, performing code reviews, and writing test cases. Collaboration with data scientists, UX designers, and product managers is common, giving you exposure to the full development lifecycle and valuable opportunities to learn from experienced colleagues.

What is the difference between Entry Level Ai Agent Developer vs Data Analyst?

AspectEntry Level Ai Agent DeveloperData Analyst
Required CredentialsBachelor's in CS, AI, or related field; basic programming skillsBachelor's in Statistics, Math, or related field; data analysis skills
Work EnvironmentTech companies, AI startups, R&D labsBusiness, finance, healthcare sectors
Employer & Industry UsageDeveloping AI agents, chatbots, automation toolsInterpreting data, creating reports, supporting decision-making

Entry Level Ai Agent Developers focus on creating and refining AI agents and chatbots, often requiring programming and AI knowledge. Data Analysts interpret data to inform business decisions, typically with statistical skills. While both roles involve data and technology, they serve different functions within organizations. The choice depends on your interest in AI development versus data interpretation.

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Entry Level Ai Agent Developer jobs near you
Infographic showing various Entry Level Ai Agent Developer job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Forward Deployed Engineer (Generative AI)

Tiger Analytics Inc.

Dallas, TX

Full-time

Re-posted 21 days ago

Job description

Tiger Analytics is looking for experienced Forward Deployment Engineer (Generative AI) with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Role Overview

The Forward Deployment Engineer (FDE) drives the on-site deployment, integration, and scaling of our enterprise Generative AI solutions. This role embeds directly within customer engineering teams to operationalize Large Language Models (LLMs) and retrieval systems across multi-cloud environments (AWS, Azure, GCP). You will bridge the gap between AI research and production-grade cloud infrastructure.

You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Requirements

Agentic Design & Implementation
Develop intelligent agents using Vertex AI Agent Builder to automate complex
business workflows.
Leverage the Agent Developer Kit (ADK) to build and manage multi-agent systems
that collaborate to solve end-to-end business challenges.
Implement tools like MCP (Model Context Protocol) Toolbox to securely connect
agents to enterprise databases like BigQuery and Spanner.


AI on Data Strategy
Utilize Vertex AI for model training, tuning, and deployment, ensuring seamless
integration with BigQuery for feature engineering.
Build and optimize streaming data pipelines (e.g., via Dataflow) to execute
real-time inference using RunInference API or Vertex AI endpoints.
Ground AI models in live business context using vector engines within BigQuery or
AlloyDB to eliminate "AI amnesia".


Operational Excellence (Soft Skills)
Active Participation: Show up promptly for all internal and client-facing meetings.
Transparent Communication: Provide regular, structured status updates to team
members and stakeholders regarding project milestones and technical blockers.
Proactive Collaboration: Demonstrate the ability to ask for help when facing
technical hurdles and contribute to a collaborative troubleshooting environment.
Consultative Approach: Navigate corporate environments to translate high-level
business goals into robust technical architectures.
Technical Qualifications
Vertex AI Mastery: Proven experience with Model Garden, Vertex AI Pipelines, and
model evaluation.
Data Proficiency: Advanced knowledge of SQL for BigQuery, Python for ML
engineering, and data preprocessing techniques (scaling, encoding, imputation).
Cloud Infrastructure: Hands-on experience with Google Cloud Storage and Vertex
AI endpoints.
Emerging Tech: Familiarity with stateful real-time processing and the latest
innovations in agentic architectures.

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

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