AI/ML & Data Engineer - Solutions & Business Development
At a glance
Mid-level Data Engineering role at Devsinc. Lahore · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and deploy AI/ML and data engineering solutions, including pipelines, warehouses and lakes
- Use Python, SQL, cloud platforms and AI approaches such as LLMs, RAG and predictive analytics
- Run client discovery, present architectures and demos, and develop proofs of concept
- Turn client needs into technical proposals, scopes, estimates and statements of work
- Work with sales, leadership and delivery teams to progress opportunities and hand projects over
What you bring
- A relevant technical degree, such as computer science, AI or data science, or a related field
- Three to five years in AI/ML, data engineering, data science or a related area
- Practical strength in Python, SQL, machine learning, data engineering and cloud technologies
- Experience delivering AI/ML or data projects, preferably in client-facing work
Who this fits
This role suits a hands-on engineer who can explain technical options in business terms and help move client opportunities from discovery toward closure. It is an onsite, full-time position in Lahore, Pakistan.
From the employer
We are looking for a highly skilled AI/ML & Data Engineer with strong technical expertise, excellent communication skills, and the ability to engage with clients and drive opportunities toward closure. The ideal candidate will combine hands-on engineering capabilities with strong business acumen - someone who can understand complex client requirements, architect the right solution, present it confidently, and help convert opportunities into successful projects.
Requirements
1. Design, develop, and deploy scalable AI/ML and Data Engineering solutions.
2. Work hands-on with Python, SQL, machine learning, data pipelines, APIs, databases, and cloud platforms.
3. Develop solutions using Generative AI, LLMs, RAG, NLP, predictive analytics, and AI/ML frameworks.
4. Design and implement data warehouses, data lakes, ETL/ELT pipelines, and data processing solutions.
5. Evaluate technical requirements and recommend the most appropriate architecture, tools, and technologies.
6. Engage directly with clients to understand their business and technical challenges.
7. Lead technical discovery calls, presentations, solution discussions, demos, and POCs.
8. Prepare technical proposals, solution architectures, project scopes, estimates, and SOWs.
9. Work closely with Sales and leadership to identify, develop, and close new project opportunities.
10. Address technical objections and communicate complex solutions in a clear, business-focused manner.
11. Build strong client relationships and identify opportunities for upselling and long-term engagements.
12. Collaborate with engineering and delivery teams to ensure successful project handover and execution.
Qualification
1. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related technical field.
2. 3–5 years of relevant professional experience in AI/ML, Data Engineering, Data Science, or a related domain.
3. Strong hands-on technical expertise with Python, SQL, Machine Learning, Data Engineering, and Cloud technologies.
4. Proven experience working on AI/ML and data-driven projects, preferably in a client-facing environment.
5. Strong communication, presentation, problem-solving, and negotiation skills.
6. Ability to understand client requirements, propose technical solutions, and contribute to winning and closing projects.
Required Skills
1. Strong hands-on technical and problem-solving capabilities.
2. Excellent verbal and written communication skills.
3. Strong client-facing, presentation, negotiation, and stakeholder-management skills.
4. Ability to translate technical solutions into clear business value.
5. Proven ability to take ownership of opportunities and drive them from discovery to closure.
6. Commercially driven, proactive, and comfortable working with both technical and business stakeholders.
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