Agentic AI Engineer must have experience in Agentic AI

About Company

Droisys is an innovation technology company focused on helping companies accelerate their digital initiatives from strategy and planning through execution. We leverage deep technical expertise, Agile methodologies, and data-driven intelligence to modernize systems of engagement and simplify human/tech interaction. Amazing things happen when we work in environments where everyone feels a true sense of belonging and when candidates have the requisite skills and opportunities to succeed. At Droisys, we invest in our talent and support career growth, and we are always on the lookout for amazing talent who can contribute to our growth by delivering top results for our clients. Join us to challenge yourself and accomplish work that matters .

 

Job Title              Agentic AI Engineer / Applied AI Engineer

Job Location      Remote Work

Duration             12 Months

Rate             $65/hr on c2c 

Final round will be in person to the nearest location

 

Job Summary

We are seeking a highly skilled Agentic AI Engineer / Applied AI Engineer to design, develop, and deploy next-generation AI systems. This role focuses on leveraging large language models (LLMs), autonomous agents, retrieval systems, and intelligent workflows to solve complex enterprise challenges.

At the 409 level (Senior Software Engineer), this position requires strong hands-on engineering expertise, sound software architecture skills, and the ability to independently lead the delivery of scalable AI-powered products and platforms. The ideal candidate combines solid software engineering fundamentals with applied AI/ML experience and thrives in fast-paced, innovation-driven environments.

 

Key Responsibilities

 

AI Agentic Systems Development

Design and implement intelligent AI agents capable of reasoning, planning, tool usage, memory management, and multi-step workflow execution.
Build production-grade LLM applications using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar orchestration platforms.
Develop retrieval-augmented generation (RAG) pipelines that integrate vector databases with enterprise knowledge systems.
Create autonomous workflows that connect APIs, tools, databases, and enterprise services.
 

Applied AI Engineering

Fine-tune, evaluate, and optimize LLMs and generative AI systems for enterprise use cases.
Develop prompt engineering strategies, evaluation pipelines, guardrails, and AI safety mechanisms.
Implement AI observability, monitoring, hallucination detection, and performance optimization solutions.
Work with structured and unstructured data pipelines for AI model consumption.
 

Software Engineering and Platform Development

Build scalable backend services and APIs using Python, Java, Node.js, or Go.
Design cloud-native AI architectures on platforms such as AWS, Azure, or GCP.
Develop microservices and containerized applications using Docker and Kubernetes.
Implement CI/CD pipelines, testing frameworks, and infrastructure-as-code practices.
 

Leadership and Collaboration

Lead technical design discussions and architecture reviews.
Mentor junior engineers and guide AI engineering best practices.
Collaborate with product managers, data scientists, architects, and business stakeholders to deliver AI-driven solutions.
Drive technical innovation and contribute to enterprise AI strategy.
 

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or a related field.
At least 5 years of software engineering experience.
At least 2 years of hands-on experience building generative AI or LLM-based applications.
Strong programming skills in Python and at least one additional language such as Java, Go, or JavaScript/TypeScript.
Experience with LLM APIs such as OpenAI, Anthropic, or open-source models.
Hands-on experience with vector databases such as Pinecone, Weaviate, FAISS, or ChromaDB.
Strong understanding of RAG architectures, semantic search, REST APIs, distributed systems, and scalable backend design.
Experience with cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform.
Strong understanding of software design patterns, system scalability, and observability.
 

Preferred Qualifications

Experience with multi-agent orchestration systems.
Familiarity with AI governance, responsible AI, and enterprise security standards.
Experience deploying AI systems in healthcare, retail, insurance, or pharmacy domains.
Knowledge of reinforcement learning, model fine-tuning, or evaluation frameworks.
Contributions to open-source AI projects or published technical research.
 

Technical Skills

 

Programming and Frameworks

Languages: Python, Java, TypeScript, Go
Frameworks and platforms: FastAPI, Flask, Spring Boot, Node.js
Agent orchestration: LangChain, LangGraph, CrewAI, AutoGen
AI/ML tooling: PyTorch, TensorFlow, Hugging Face
 

AI and Data Technologies

LLMs and generative AI
Retrieval-augmented generation (RAG)
Vector databases
Prompt engineering
AI evaluation frameworks
NLP and semantic search
 

Cloud and DevOps

Cloud platforms: AWS, Azure, GCP
Containerization and orchestration: Docker, Kubernetes
Infrastructure as code: Terraform
CI/CD tools: GitHub Actions, Jenkins
Monitoring and observability tools
 

Senior-Level Expectations

Independently own large technical initiatives end to end.
Make architectural decisions with long-term scalability in mind.
Drive engineering excellence and operational maturity.
Influence technical direction across teams.
Balance rapid experimentation with production-grade engineering discipline.
 

Nice-to-Have Experience

Healthcare or pharmacy technology experience.
Experience building conversational AI platforms or enterprise copilots.
Knowledge of HIPAA compliance and regulated AI environments.
Exposure to graph-based orchestration and workflow engines.
 

 

 

Droisys is an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. Droisys believes in diversity, inclusion, and belonging, and we are committed to fostering a diverse work environment.