Senior AI Engineer

Job Description

Title: Senior AI Engineer

Company Name: Boston AI Partners

Vacancy: --

Age: At least 25 years

Job Location: Dhaka, United States

Salary: Tk. 100000 - 130000 (Monthly)

Experience:

Published: 2026-07-20

Application Deadline: 2026-07-30

Education:

• Bachelor/Honors

• Age At least 25 years

Role Summary

We are seeking a highly skilled Senior AI Engineer to lead the design, development, and deployment of

practical AI solutions for real business use cases. The ideal candidate will have strong hands-on experience

with machine learning, generative AI, large language models, AI agents, Python-based backend

development, cloud deployment, and production-grade software engineering practices.

This role is intended for a senior engineer who can move beyond experiments and prototypes to build

reliable, scalable, secure, and maintainable AI systems. The candidate should be comfortable working with

business stakeholders, product teams, and developers to translate ambiguous requirements into working AI

products.

About the Role

• The Senior AI Engineer will be responsible for building AI-powered applications, intelligent automation workflows, AI agents, retrieval-augmented generation systems, model integrations, and custom machine

• learning solutions. The engineer will help shape technical architecture, select appropriate tools and models, guide implementation, review code, improve system performance, and support deployment to production environments.

• This is a high-impact role for someone who wants to work on real-world AI projects across areas such as document intelligence, enterprise assistants, workflow automation, computer vision, quality control, data extraction, decision support systems, and custom AI tools for clients.
  

Key Responsibilities

 Design, develop, and deploy production-ready AI and machine learning solutions aligned with business

requirements.

 Build and optimize AI agents, LLM-powered applications, RAG pipelines, prompt workflows, and tool-using agent architectures.

 Develop backend services and APIs using Python frameworks such as FastAPI, Django, or Flask.

 Integrate large language models, embedding models, vector databases, and external APIs into scalable

applications.

 Fine-tune, evaluate, and optimize machine learning or deep learning models where required.

 Build data processing pipelines for cleaning, transforming, labeling, and preparing structured and

unstructured datasets.

 Implement model evaluation processes, including accuracy, latency, reliability, hallucination risk, cost,

and performance metrics.

 Work with cloud platforms such as Azure, AWS, or Google Cloud to deploy AI services securely and efficiently.

 Collaborate with frontend, backend, QA, product, and business teams to deliver complete AI-enabled products.

 Write clean, maintainable, testable, and well-documented code following professional software engineering standards.

 Review code, mentor junior engineers, and support the team in improving AI engineering best practices.

 Implement automated testing, monitoring, logging, CI/CD pipelines, and performance optimization for AI systems.

 Ensure responsible AI practices, including data privacy, security, model reliability, and ethical use of AI technologies.

 Troubleshoot technical issues across AI models, backend services, data pipelines, cloud infrastructure, and application layers.

Required Qualifications

 Bachelor's degree in Computer Science, Software Engineering, Machine Learning, Data Science, Electrical

Engineering, or a related technical field. Equivalent professional experience may be considered.

 5+ years of professional software engineering experience, with at least 2+ years focused on AI, machine

learning, data science, LLM applications, or AI product development.

 Strong proficiency in Python and experience building production-grade backend systems.

 Hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, LlamaIndex, Semantic Kernel, or similar tools.

 Practical experience building AI agents, LLM applications, chatbots, RAG systems, or intelligent automation workflows.

 Experience working with APIs, REST services, databases, authentication, background jobs, and scalable application architecture.

 Experience with vector databases or search technologies such as Pinecone, Weaviate, Milvus, FAISS, Chroma, Azure AI Search, Elasticsearch, or similar systems.

 Strong understanding of model evaluation, prompt engineering, embeddings, retrieval quality, data quality, and performance optimization.

 Experience with SQL and NoSQL databases such as PostgreSQL, MySQL, MongoDB, Redis, or similar technologies.

 Familiarity with Docker, Git, GitHub/GitLab, CI/CD pipelines, and modern development workflows.

 Strong problem-solving ability and the capability to independently debug complex technical issues.

 Good written and verbal communication skills in English, with the ability to explain technical ideas clearly to both technical and non-technical stakeholders.

Preferred Qualifications

 Master's degree in Computer Science, AI, Machine Learning, Data Science, or a related field.

 Experience deploying AI applications on Microsoft Azure, especially Azure OpenAI, Azure AI Search, Azure Machine Learning, Azure Functions, App Service, AKS, or related services.

 Experience with OpenAI, Anthropic, Google Gemini, Meta Llama, Mistral, Qwen, or other commercial/open-source LLMs.

 Experience with MLOps, model monitoring, experiment tracking, model versioning, and deployment tools such as MLflow, Weights & Biases, DVC, or similar platforms.

 Experience with computer vision, OCR, document processing, object detection, or image-based AI systems.

 Experience with frontend technologies such as ReactJS, Next.js, TypeScript, or modern UI integration is a plus.

 Experience working in Agile/Scrum environments and participating in sprint planning, estimation, UAT support, and production releases.

 Experience working with international clients, distributed teams, or US-based business stakeholders.

Technical Skill Expectations

• AI / ML LLMs, RAG, embeddings, AI agents, prompt engineering, fine-tuning, model evaluation, data pipelines, NLP, computer vision exposure

• Programming Python required; JavaScript/TypeScript preferred; strong API and backend development capability

• Frameworks FastAPI, Django, Flask, PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, LlamaIndex, or equivalent

• Data / Search PostgreSQL, MongoDB, Redis, vector databases, semantic search,

• Elasticsearch/Azure AI Search, data cleaning and transformation

• Cloud / DevOps Azure, AWS, or GCP; Docker; CI/CD; GitHub Actions; monitoring, logging, secure deployment practices

• Engineering Practices Clean code, testing, documentation, code review, architecture decisions, scalability, security, and maintainability

Soft Skills and Leadership Expectations

 Ability to take ownership of complex AI workstreams from requirement analysis to delivery.

 Strong communication skills and ability to provide clear technical updates to leadership.

 Ability to mentor junior engineers and improve team-level AI development practices.

 Business-focused mindset with the ability to understand client problems before proposing technical

solutions.

 Comfortable working in a fast-moving startup or consulting environment where priorities may evolve.

 High integrity, confidentiality, and professionalism when handling client data and business-sensitive

information.

Example Projects the Candidate May Work On

 Enterprise AI assistants for internal knowledge search, document Q&A, and workflow automation.

 AI-powered document intelligence systems for extracting, classifying, and validating information from

PDFs, forms, and reports.

 Custom LLM applications with retrieval, structured outputs, tool-calling, and human-in-the-loop review.

 Computer vision solutions for image analysis, quality inspection, object detection, or operational

monitoring.

 AI automation tools that reduce manual business processes and improve operational efficiency for

clients.

 Internal AI engineering frameworks, reusable components, and deployment templates for faster project

delivery.

Success Measures for the Role

 Delivers AI features and prototypes that can be moved toward production, not only proof-of-concept

demos.

 Improves model accuracy, response quality, latency, reliability, and cost-efficiency through measurable

engineering work.

 Creates clear technical documentation, architecture notes, and handover materials for internal and client

teams.

 Helps the company build reusable AI engineering capabilities that reduce delivery time across future

projects.

 Communicates risks, assumptions, blockers, and technical trade-offs early and clearly to leadership.

Work Arrangement

 Remote-first working arrangement, with availability for scheduled meetings, sprint discussions, client calls, and technical reviews.

 Must have a reliable computer, stable internet connection, and professional remote-work setup.

 Expected to maintain strong availability, accountability, and communication during agreed working

hours.

 Occasional flexibility may be required to coordinate with US Eastern Time Zone meetings, depending on

client needs.

Application Requirements

 Updated resume or CV.

 GitHub profile, portfolio, project links, or examples of relevant AI/ML work, if available.

 Brief explanation of past AI/LLM/ML projects, including the candidate's specific role and technical

contribution.

 Expected monthly compensation in BDT or USD equivalent.

 Earliest available start date and preferred employment arrangement.

Why Join Us

 Opportunity to work on practical, real-world AI solutions for business clients.

 Exposure to modern AI tools, LLM applications, automation, cloud deployment, and product development.

 Opportunity to take ownership of meaningful technical decisions and grow into a technical leadership

role.

 Collaborative team culture focused on learning, execution, and measurable client value.

 Flexible, remote-friendly work environment with room for professional growth.