AI Engineer
7 days ago
Job Title: AI Engineer
Location:
Remote/Hybrid
Department:
Technology & Innovation
Experience Level:
Mid-Senior (4–6 years)
Employment Type:
Full-Time
About MAF Group
At MAF Group, we empower enterprises to harness the transformative power of
AI, Data, and Cloud technologies
. We help organizations innovate, optimize, and scale with cutting-edge solutions tailored to their business needs. As we expand our
AI/GenAI practice
, we are seeking passionate professionals who can shape the future of intelligent systems and automation.
About the Role
We are hiring an
AI Engineer
who will play a critical role in designing, developing, and deploying advanced AI solutions. This role involves building
Generative AI applications, integrating AI with enterprise systems, and creating scalable, production-ready pipelines
that address real-world business challenges across industries.
Key Responsibilities
- Design, develop, and optimize AI/ML models for diverse enterprise use cases.
- Build and deploy
GenAI applications
leveraging LLMs, RAG frameworks, and agentic workflows. - Implement embeddings, vector databases, and prompt engineering to improve intelligent search and retrieval.
- Integrate AI solutions with APIs, microservices, and cloud platforms (
AWS, Azure, GCP
). - Collaborate with data engineers and software developers to ensure scalable AI pipelines.
- Conduct model evaluation, fine-tuning, and performance optimization.
- Stay ahead of emerging trends in
AI, ML, GenAI, and automation
technologies.
Required Skills & Qualifications
- Bachelor's/Master's in
Computer Science, AI/ML, Data Science
, or related field. - Proficiency in
Python
and frameworks such as
PyTorch, TensorFlow, LangChain, LangGraph
. - Strong hands-on experience with
LLMs, embeddings, and RAG architecture
. - Familiarity with
cloud AI services
(AWS Bedrock, Azure OpenAI, Google Vertex AI). - Experience with APIs, microservices, and
RESTful integrations
. - Knowledge of
NLP, data preprocessing, and model fine-tuning
. - Solid understanding of
MLOps
practices (CI/CD for ML, model monitoring, lifecycle).
Preferred Qualifications
- Experience with
agentic AI workflows
and multi-agent systems. - Knowledge of
vector databases
(Pinecone, Weaviate, Milvus, FAISS). - Exposure to
Docker, Kubernetes
, and scalable deployment methods. - Prior experience delivering
enterprise-grade AI solutions
across industries.
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