Lead Generative AI Engineer

Key Responsibilities

• Define the architecture engineering standards and technical direction for enterprise GenAI platforms and applications.
• Architect scalable secure reliable and cost-efficient AI platforms infrastructure and reusable AI services.
• Design and productionize advanced RAG pipelines including ingestion chunking embeddings vector retrieval reranking context management and evaluation.
• Establish best practices for LLMOps prompt management agent orchestration AI observability model evaluation guardrails and AI governance.
• Lead the development of enterprise AI copilots conversational BI solutions AI-powered customer service assistants recommendation engines knowledge retrieval systems and autonomous workflow agents.
• Design sophisticated multi-agent and tool-calling workflows integrated with enterprise APIs databases applications and external services.
• Drive GenAI solutions from architecture and proof-of-concept through production deployment scaling monitoring and optimization.
• Optimize latency throughput GPU utilization inference cost scalability reliability and model performance.
• Implement strategies for hallucination mitigation AI evaluation security privacy Responsible AI and enterprise compliance.
• Evaluate emerging LLMs AI frameworks inference technologies vector databases and orchestration platforms to guide the enterprise AI technology roadmap.
• Mentor AI/ML and GenAI engineers and provide technical leadership across multiple AI initiatives.
• Partner with business product and technology stakeholders to convert high-impact business opportunities into scalable AI solutions.
• Contribute to enterprise AI strategy architecture governance and technology roadmap.

Required Experience

• 7 years of professional experience across AI/ML engineering software engineering distributed systems enterprise platforms or related areas.
• Proven experience architecting developing and deploying production-grade AI/GenAI systems at scale.
• Strong hands-on experience taking AI solutions from concept and architecture to production deployment and optimization.
• Previous experience leading technical teams AI engineering squads or providing architecture and engineering leadership.

Qualifications :

Technical Expertise

Generative AI & LLM Engineering: LLM application development prompt engineering RAG architectures semantic search embeddings vector retrieval AI agents tool/function calling multi-agent orchestration context and memory management model evaluation guardrails and hallucination mitigation.

Backend & Platform Engineering: Strong proficiency in Python backend/API engineering FastAPI or equivalent frameworks distributed systems scalable architectures and enterprise integrations.

GenAI Ecosystem: Hands-on experience with technologies such as LangChain LlamaIndex MLflow vector databases AI evaluation/observability tools and agent orchestration frameworks.

AI Infrastructure & LLMOps: Experience with GPU-based inference open-source LLM deployment model serving LoRA/PEFT fine-tuning distributed AI workloads Docker Kubernetes CI/CD DevOps and cloud-native AI architectures.

Cloud Platforms: Hands-on familiarity with one or more major cloud ecosystems AWS Microsoft Azure or Google Cloud Platform (GCP).

Leadership & Professional Capabilities

We are looking for someone who can combine strategic thinking with hands-on technical execution. The ideal candidate should demonstrate strong architecture and technical decision-making skills the ability to mentor engineers experience with AI governance and Responsible AI excellent problem-solving capability and strong stakeholder communication and presentation skills.

The candidate should be comfortable leading multiple AI initiatives with minimal supervision while collaborating effectively with engineering product business security and leadership teams.

Academic Qualification

Bachelors or Masters degree in Computer Science Software Engineering Artificial Intelligence Data Science Applied Statistics Information Technology Business/Analytics or another relevant discipline.

Additional Information :

Preferred Qualifications

Experience in any of the following will be considered an advantage: enterprise-scale RAG and Agentic AI systems; open-source LLM deployment and optimization; GPU/inference infrastructure; LLMOps or enterprise AI platform architecture; AI governance and compliance; high-volume or mission-critical applications; relevant AI/cloud certifications; open-source contributions; patents; research publications; or conference presentations.

Why Join Flyte Solutions Ltd.

At Flyte Solutions Ltd. you will have the opportunity to work on sophisticated enterprise AI initiatives and contribute to solutions that move beyond experimentation into real-world production-grade Generative AI.

Our core service portfolio focuses on Technology Resource Augmentation and Managed Services with capabilities spanning Generative AI & AI/ML Software Engineering QA & Automation Cloud & DevOps Database Engineering Application Support Infrastructure and Technology Operations.

If you are passionate about building enterprise AI platforms RAG systems intelligent agents and production-grade GenAI applications and want to take technical ownership of challenging AI initiatives we would be interested in speaking with you.

Position: Lead Generative AI Engineer
Employment Type: Full-Time
Company: Flyte Solutions Ltd.
Location: Bangladesh
Experience: 7 Years

Interested candidates are encouraged to apply by sharing their updated CV with Flyte Solutions Ltd.

How to Apply

Please send your updated CV to career(@)

Email Subject: Lead AI Engineer7Years

Only candidates closely matching the required experience and technical profile will be shortlisted.

Please include:

• Updated Resume/CV
• Current Salary
• Expected Salary
• Notice Period
• GitHub Profile (Preferred)
• LinkedIn Profile (Preferred)

Flyte Solutions Ltd.
Morning Glory Level 6 & 7
House 19 Road 13/C Block-E
Banani Dhaka 1213 Bangladesh

Remote Work :

No

Employment Type :

Full-time