The Role
Design, build, and deploy agentic AI systems and multi-agent frameworks; integrate agents with enterprise platforms; monitor and refine agent behavior; implement RAG/vector DB retrieval; handle model deployment (APIs/microservices); mentor engineers and contribute to AI architecture and roadmaps.
Summary Generated by Built In
Job Summary
We are seeking a talented Agentic AI Engineer to design,
develop, and deploy advanced AI agents capable of autonomous reasoning,
decision-making, and self-directed task execution. This role
requires expertise in modern AI architecture, reinforcement learning,
multi-agent solution frameworks, and the deployment of agentic AI
solutions. You will collaborate with cross-functional teams to create
intelligent systems that drive business value and innovation.
Key Responsibilities
- Design and Development: Build and optimize agentic
AI systems (e.g., autonomous agents, multi-agent frameworks, LLM-powered
agents, MCP, RAG, Agent Skills, Context Engineering, Agent Memory)
- Integrate agentic AI
solutions with existing enterprise platforms and workflows.
- Work closely with
product, data, and engineering teams to translate business requirements
into AI solutions
- Monitor
agent behaviors, diagnose anomalies, and refine
agent instructions as needed
- Deploying agentic AI agents in
production environments, ensuring reliability and performance
- Developed feedback loops
for continuous agent improvement
- Conduct code reviews and
mentor junior engineers
- Contribute to AI
architecture, technical standards, and roadmap planning
Required Skills & Qualifications
- 6+ years of
hands-on experience in Artificial Intelligence, Machine Learning, or
related field.
- Knowledge of developing
Gen AI or AI/ML solutions from use case to production and an understanding
of agentic or autonomous systems.
- Understanding of
Infrastructure and DevOps related to Gen AI Use case deployments including
Cloud environments, Agent Hosting, CICD deployments, docker and
Kubernetes.
- Proficiency in Python development
and FastAPI/Flask
framework along with SQL
- Expertise with
agentic AI frameworks and concepts - LangChain, LangGraph, ADK, AutoGen, Model
Context Protocol (MCP), LLMs, Chain of Thought prompting, knowledge store,
embeddings
- Experience with RAG
techniques for knowledge base retrievals from vector DB.
- Prompt engineering
techniques and fine-tuning
- Hands-on experience
with model deployment (REST APIs, microservices, or
cloud-based inference)
- Hands-on experience with
building user experiences to support agent-based solutions.
- Experience with cloud
platforms (AWS, Azure, or GCP) and AI services
- Strong problem-solving
and analytical skills
- Excellent communication
and cross-functional collaboration abilities
Preferred / Nice-to-Have Skills
- Understanding of:
- Machine Learning
algorithms
- Deep Learning (CNNs,
RNNs, Transformers)
- Natural Language
Processing (NLP) and/or Computer Vision
- Experience with data
processing and analysis using NumPy, Pandas, and SQL
- Familiarity
with MLOps practices (model versioning, monitoring, CI/CD)
- Experience with Generative
AI and LLMs (OpenAI, Hugging Face, LangChain, RAG
pipelines)
- Experience with big data
tools (Spark, Kafka)
- Familiarity with ethical
AI, bias mitigation, and model governance
- Prior experience leading
AI initiatives or mentoring teams
What We Offer
- Competitive compensation
and benefits
- Flexible work
arrangements
- Opportunity to work
on cutting-edge AI and GenAI projects
- Continuous learning and
professional development
- Collaborative and
innovation-driven culture
Skills Required
- 6+ years of hands-on experience in Artificial Intelligence, Machine Learning, or related field
- Experience developing GenAI or AI/ML solutions from use case to production and understanding of agentic/autonomous systems
- Understanding of infrastructure and DevOps for GenAI deployments including cloud environments, agent hosting, CI/CD, Docker, and Kubernetes
- Proficiency in Python development and FastAPI/Flask framework along with SQL
- Expertise with agentic AI frameworks and concepts (LangChain, LangGraph, ADK, AutoGen, MCP, LLMs, chain-of-thought prompting, knowledge stores, embeddings)
- Experience with RAG techniques for knowledge base retrievals from vector databases
- Prompt engineering techniques and fine-tuning
- Hands-on experience with model deployment (REST APIs, microservices, or cloud-based inference)
- Hands-on experience building user experiences to support agent-based solutions
- Experience with cloud platforms (AWS, Azure, or GCP) and AI services
- Strong problem-solving and analytical skills
- Excellent communication and cross-functional collaboration abilities
- Understanding of machine learning algorithms
- Deep learning (CNNs, RNNs, Transformers)
- Natural Language Processing (NLP) and/or Computer Vision experience
- Experience with data processing and analysis using NumPy and Pandas
- Familiarity with MLOps practices (model versioning, monitoring, CI/CD)
- Experience with Generative AI and LLMs (OpenAI, Hugging Face, LangChain, RAG pipelines)
- Experience with big data tools (Spark, Kafka)
- Familiarity with ethical AI, bias mitigation, and model governance
- Prior experience leading AI initiatives or mentoring teams
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The Company
What We Do
SID Global Solutions (SIDGS) is an AI-first digital transformation and consulting company serving enterprises worldwide. It delivers intelligent full-stack solutions across artificial intelligence, cloud modernization, automation, API and application transformation, and enterprise intelligence. SIDGS helps organizations modernize legacy systems, optimize operations, integrate data and platforms, and accelerate measurable digital growth through scalable, customer-centric technology services for complex and demanding enterprise environments.
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