ONLY W2, NO C2C
Software Engineer (AI/Agentic AI Engineer)
Hybrid Tampa, FL or Jersey City or Dallas (3x Days onsite)
6+ Months Contract
INTERVIEW TYPE 2 Rounds
Software Engineering
5 8 years of professional software development experience.
Strong programming skills in Python and/or Java, SQL.
Experience building scalable, maintainable, and production-grade applications.
Experience supporting enterprise data platforms and cloud-based data solutions in production environments.
Strong experience working with large data volumes, data processing, and SQL/query optimization.
Strong understanding of:
REST APIs
Microservices
Event-driven architecture
Databases
Git-based development
Automated testing
CI/CD pipelines
Containerization technologies such as Kubernetes/OpenShift
Strong knowledge of software design principles and architectural patterns.
Strong understanding of distributed and cloud-based data technologies.
Generative AI & Large Language Models
Hands-on experience building applications using Generative AI and LLM technologies.
Experience with prompt engineering and structured LLM interactions.
Knowledge of:
Retrieval Augmented Generation (RAG)
Embeddings
Vector search and vector databases
Context management and grounding techniques
Experience integrating LLMs through APIs and SDKs.
Experience with at least one cloud AI platform such as:
AWS Bedrock
Snowflake Cortex
Agentic AI Development
Hands-on experience designing and implementing AI agents and agentic workflows.
Strong understanding of:
Planning and task decomposition
Tool and function calling
Multi-agent systems
Memory and context management
Human-in-the-loop workflows
Agent orchestration
Reflection and validation patterns
Error handling and recovery strategies
Experience with agent orchestration technologies.
Experience building agents that integrate with enterprise applications, APIs, databases, and developer tools.
AI-Assisted Development
Minimum 2 years of practical experience using AI-powered development assistants.
Strong hands-on experience with Kiro and Claude for software development.
Demonstrated ability to effectively use AI assistants for:
Requirements analysis
Specification generation
Solution architecture
Code generation
Refactoring
Test generation
Debugging
Documentation
Code reviews
Developer productivity automation
Proven ability to validate and enhance AI-generated code rather than relying solely on generated outputs.
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