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Agentic AI Engineer Job Opening In us – Now Hiring Tiger Analytics


Job description

Tiger Analytics is looking for experienced Agentic AI Engineer 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.

You will be responsible for:

  • Providing solutions for the deployment, execution, validation, monitoring, and improvement of MLE solutions
  • Creating Scalable Machine Learning systems .
  • Building reusable production data pipelines for implemented machine learning models
  • Writing production-quality code and libraries that can be packaged as containers, installed and deployed

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

Technical Skills Required:

·        Programming Languages: Proficiency in Python is essential; C++ experience is ideal but not required.

·        Agentic AI : Expertise in LangChain/LangGraph, CrewAI, Semantic Kernel/Autogen and Open AI Agentic SDK

·        Machine Learning Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, and AutoML.

·        Generative AI: Hands-on experience with generative AI models, RAG (Retrieval-Augmented Generation) architecture, and Natural Language Processing (NLP).

·        Cloud Platforms: Familiarity with AWS (SageMaker, EC2, S3) and/or Google Cloud Platform (GCP).

·        Data Engineering: Proficiency in data preprocessing and feature engineering.

·        Version Control: Experience with GitHub for version control.

·        Development Tools: Proficiency with development tools such as VS Code and Jupyter Notebook.

·        Containerization: Experience with Docker containerization and deployment techniques.

·        Data Warehousing: Knowledge of Snowflake and Oracle is a plus.

·        APIs: Familiarity with AWS Bedrock API and/or other GenAI APIs.

·        Data Science Practices: Skills in building models, testing/validation, and deployment.

·        Collaboration: Experience working in an Agile framework.

Desired Skills:

·        RAG Architecture: Experience with data ingestion, data retrieval, and data generation using optimal methods such as hybrid search.

·        Insurance/Financial Domain: Knowledge of the insurance industry is a big plus.

·        Google Cloud Platform: Working knowledge is a plus.

Additional Expertise:

·        Industry Experience: 8+ years of industry experience in AI/ML and data engineering, with a track record of working in large-scale programs and solving complex use cases using GCP AI Platform/Vertex AI.

·        Agentic AI Architecture: Exceptional command in Agentic AI architecture, development, testing, and research of both Neural-based & Symbolic agents, using current-generation deployments and next-generation patterns/research.

·        Agentic Systems: Expertise in building agentic systems using techniques including Multi-agent systems, Reinforcement learning, flexible/dynamic workflows, caching/memory management, and concurrent orchestration.

Proficiency in one or more Agentic AI frameworks such as LangGraph, Crew AI, Semantic Kernel, etc.

·        Python Proficiency: Expertise in Python language to build large, scalable applications, conduct performance analysis, and tuning.

·        Prompt Engineering: Strong skills in prompt engineering and its techniques including design, development, and refinement of prompts (zero-shot, few-shot, and chain-of-thought approaches) to maximize accuracy and leverage optimization tools.

·        IR/RAG Systems: Experience in designing, building, and implementing IR/RAG systems with Vector DB and Knowledge Graph.

·        Model Evaluation: Strong skills in the evaluation of models and their tools.

Experience in conducting rigorous A/B testing and performance benchmarking of prompt/LLM variations, using both quantitative metrics and qualitative feedback.

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.

Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your Agentic AI Potential: Insight & Career Growth Guide


Real-time Agentic AI Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for Agentic AI in us, United States, highlighting market share and opportunities for professionals in Agentic AI roles.

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Are You Looking for Agentic AI Engineer Job?

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Tiger Analytics adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying United States laws and regulations

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The average salary range for a varies, but the pay scale is rated "Standard" in us. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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Key qualifications for Agentic AI Engineer typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for Agentic AI Engineer Job Success

Tiger Analytics interview tips for Agentic AI Engineer

Here are some tips to help you prepare for and ace your Agentic AI Engineer job interview:

Before the Interview:

Research: Learn about the Tiger Analytics's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

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Follow Up: Send a thank-you email to the interviewer within 24 hours.

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Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

Be Positive: Focus on your strengths and accomplishments.

Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Agentic AI Engineer interview at Tiger Analytics, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Tiger Analytics's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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