Lead Generative AI Engineer

Posted 29 Days Ago
Be an Early Applicant
Dhaka, BGD
In-Office
Senior level
Artificial Intelligence • Fintech • Information Technology • Software
The Role
Lead the architecture, development, and production deployment of enterprise Generative AI platforms and applications. Design scalable RAG pipelines, multi-agent workflows, copilots, conversational BI, and AI assistants. Establish LLMOps, evaluation, observability, guardrails, governance, and security practices. Optimize inference performance, cost, reliability, and scalability while evaluating emerging AI technologies. Mentor engineers, provide technical leadership, and partner with stakeholders to deliver production-grade AI solutions.
Summary Generated by Built In
Company Description

Flyte Solutions Ltd. is looking for an accomplished Lead Generative AI Engineer to drive the architecture, engineering, and production deployment of enterprise-scale Generative AI solutions.

This is a senior technical leadership and hands-on engineering role for someone with deep expertise in LLMs, RAG, Agentic AI, LLMOps, AI infrastructure, and distributed systems. The successful candidate will help shape enterprise AI architecture while leading the development of secure, scalable, reliable, and cost-efficient AI platforms and applications.

Job Description

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

Bachelor’s or Master’s 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(@)flytesolutions.com

Email Subject: Lead AI Engineer_7Years

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

🌐 https://www.flytesolutions.com

Skills Required

  • 7+ years of professional experience in AI/ML engineering, software engineering, distributed systems, enterprise platforms, or related areas
  • Experience architecting, developing, and deploying production-grade AI or Generative AI systems at scale
  • Experience taking AI solutions from concept and architecture through production deployment and optimization
  • Experience leading technical teams, AI engineering squads, or providing architecture and engineering leadership
  • Strong proficiency in Python
  • Backend and API engineering experience, including FastAPI or equivalent frameworks
  • Experience with distributed systems, scalable architectures, and enterprise integrations
  • Hands-on experience with LLM application development, prompt engineering, RAG, semantic search, embeddings, vector retrieval, AI agents, tool calling, multi-agent orchestration, context and memory management, model evaluation, guardrails, and hallucination mitigation
  • Experience with LangChain, LlamaIndex, MLflow, vector databases, AI evaluation or observability tools, and agent orchestration frameworks
  • Experience with GPU-based inference, open-source LLM deployment, model serving, LoRA or PEFT fine-tuning, distributed AI workloads, Docker, Kubernetes, CI/CD, DevOps, and cloud-native AI architectures
  • Familiarity with AWS, Microsoft Azure, or Google Cloud Platform
  • Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, Applied Statistics, Information Technology, Business/Analytics, or a relevant discipline
  • Experience with enterprise-scale RAG and Agentic AI systems
  • Experience with open-source LLM deployment and optimization
  • Experience with GPU or inference infrastructure
  • Experience with LLMOps or enterprise AI platform architecture
  • Experience with AI governance and compliance
  • Experience supporting high-volume or mission-critical applications
  • Relevant AI or cloud certifications
  • Open-source contributions, patents, research publications, or conference presentations
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The Company
149 Employees
Year Founded: 2012

What We Do

Flyte Solutions Ltd. is a client-focused custom software development company providing strategic, ROI-driven digital solutions tailored to business needs. Specializing in custom software, SaaS platforms, MVP development, and IT staff augmentation, the company builds scalable, innovative, and cost-effective software products for startups, SMEs, and large enterprises. Their expertise spans multiple sectors, including fintech, healthcare, and manufacturing, leveraging modern technology stacks to drive efficiency and growth.

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