Mahabub (H) Akram
Team Lead – Engagement & Relevance
Experience
Team Lead – Engagement & Relevance
OLX eCommerce
- Lead a cross-functional squad of backend, frontend, and ML/data engineers, balancing hands-on contribution (architecture, coding, reviews) with team leadership (mentoring, backlog prioritization, roadmap alignment).
- Designed and delivered ML-powered search and discovery features, including Learning-to-Rank (LTR), query expansion, and vector search, improving result relevance and user engagement.
- Implemented personalization and recommendation pipelines, using behavioral data and segmentation to increase customer retention and lifetime value.
- Established data-driven practices, building A/B testing and experimentation workflows (Odyn, MLflow) to measure feature impact on CTR, NDCG, and conversion.
- Owned the squad’s architecture and delivery roadmap, modernizing services with cloud-native microservices and event-driven systems (AWS, Pulumi, Terraform) to improve scalability and reliability.
- Improved reliability and operational excellence, introducing observability (Prometheus, Grafana, NewRelic), incident management, and postmortems that reduced downtime for customer-facing services.
- Mentored and supported engineers, fostering technical growth, collaboration, and a customer-first mindset through regular feedback, coaching, and code reviews.
- Worked closely with product managers, researchers, and business stakeholders to translate customer insights into technical solutions that improved discovery, engagement, and retention.
- Explored Generative AI/LLM use cases (GPT-4, LangChain, RAG), prototyping intelligent assistants and personalized discovery workflows that increased user satisfaction.
- Delivered tangible results: boosted engagement through personalization, contributed to revenue uplift, and reduced incidents by embedding resilience and observability.
Lead Engineer – Relevance & Engagement
OLX eCommerce
- Acted as Lead Engineer, hands-on in design and development of ML-driven discovery, recommendation, and engagement services powering millions of daily users across 12 European markets.
- Guided and implemented core features: Learning-to-Rank (LTR) models, semantic query expansion, vector embeddings, and personalized ranking pipelines to improve discovery, retention, and engagement.
- Built and extended experimentation frameworks and A/B testing pipelines (MLflow) to evaluate search and recommendation improvements with robust metrics (CTR, NDCG, conversion).
- Owned the architectural roadmap for discovery and engagement, migrating legacy monoliths to cloud-native microservices and event-driven systems (AWS, Kubernetes, Terraform) supporting near real-time ML inference at scale.
- Contributed code and reviewed critical components, ensuring reliability, scalability, and best practices in search engineering and ML model deployment.
- Mentored engineers and technical leads, guiding them in development, experimentation design, and resilient architecture; aligned closely with product managers, business stakeholders, and data scientists to translate business goals into technical solutions.
- Delivered measurable outcomes: +13.7% marketplace revenue uplift from ML-enhanced relevance features, and –30% incidents by embedding observability (Prometheus, Grafana, NewRelic) and resilient system design.
Team Lead Engineering – Depot Banking & Discovery Platform
Union Investment
- Led and shaped a cross-functional organization of engineers and ML engineers, balancing hands-on technical leadership (architecture, code reviews, prototyping) with strategic leadership (team development, stakeholder alignment, delivery roadmaps).
- Directed the modernization of mission-critical banking platforms (Depot, Banking Workspace, Integration Services), migrating from monoliths to cloud-native microservices and event-driven architectures on OpenShift, ensuring regulatory resilience, scalability, and high availability.
- Applied advanced analytics, tracking data, and A/B testing to understand customer behavior, optimize user flows, and improve satisfaction scores along the B2B and B2C customer journeys.
- Designed search and retrieval services, optimizing ranking and relevance for high-volume financial data queries using ElasticSearch, NLP, and ML models.
- Innovated with AI/ML for customer engagement and personalization, building pipelines with MLflow, Airflow, and Kafka to enable predictive modeling, personalized recommendations, and intelligent decision support.
- Strengthened reliability and operational excellence by introducing SLA/SLO-driven observability, structured incident management, and 3rd-level support; downtime reduced by 20%, improving trust and loyalty across critical banking services.
- Established governance and compliance frameworks, embedding Secure SDLC, dependency scanning, and CI/CD pipelines (GitLab CI, Jenkins) to ensure predictable, auditable, and secure delivery in a regulated financial environment.
- Mentored and developed senior engineers and team leads, fostering ownership, technical excellence, and customer-first thinking; instituted career growth frameworks and peer-learning practices to scale leadership capacity.
- Collaborated closely with Finance, Risk, Marketing, and Product stakeholders, translating business goals and compliance demands into technical solutions; secured buy-in for AI-driven engagement strategies and platform upgrades.
- Delivered both immediate impact and long-term innovation: initiated exploratory work on semantic search, personalization, and AI-enhanced customer journeys to future-proof platforms.
Lead Engineer – B2B eCommerce
MAN Truck & Bus SE (Volkswagen Group)
- Spearheaded the setup and launch of a high-traffic B2B eCommerce platform for After-Sales and Parts, enabling digital order management, advanced parts catalog search, and seamless ERP/CRM integration across VW/MAN service networks.
- Designed and implemented core search and discovery features using Java (Spring Boot), Python, and ElasticSearch to deliver scalable, reliable, and intuitive experiences for enterprise customers.
- Optimized search engine ranking and relevance, leveraging tracking data, analytics, and user behavior signals; applied NLP techniques (semantic search, entity recognition) and ML models (TensorFlow, scikit-learn) for personalization and query understanding.
- Migrated legacy monoliths to cloud-native microservices, deployed on AWS, Docker, Kubernetes; introduced event-driven and service patterns to ensure scalability, compliance, and long-term maintainability.
- Built operational excellence for a high-traffic eCommerce environment: established structured incident management and 3rd-level support processes, introduced observability (SLA/SLO dashboards, proactive monitoring), and reduced MTTR by 25%.
- Provided mentorship and technical leadership to engineers, fostering growth through code reviews, career development paths, and peer learning sessions; cultivated a strong culture of ownership, collaboration, and delivery consistency.
- Collaborated with product managers, data scientists, and strategic partners (RIO, Scania, Harman) to align eCommerce, search, and AI/ML solutions with customer needs and industry roadmaps.
Senior Software Engineer / Consultant
ARS Consulting → IBM
- Built enterprise web applications (IBM License Management Tool, Datev e-Termin) with Angular, Node.js, and Python/Django.
- Supported consulting projects with scalable, secure solution design and integrations.
Engineering Lead – E-Commerce Startup
Combyne GmbH
- Scaled the engineering team from Seed to Series A, delivering core ERP/E-Commerce features.
- Introduced modular frameworks and automation to improve reliability and release cadence by 30%.
Software Engineer
Tiger IT LTD
- Developed biometric recognition modules (Finger & Palm Vein AFIS) achieving 98.7% accuracy for high-security ID programs.
Summary
Engineering Leader with 13+ years of experience building high-traffic platforms, relevance and discovery, and customer engagement solutions. Proven ability to lead squads and mentor engineers while actively contributing to architecture, coding, and experimentation. Skilled in search relevance, personalization, and ML/AI-driven features, and experienced in using A/B testing and analytics to guide product decisions. Adept at balancing technical depth with business alignment, ensuring scalability, reliability, and measurable impact in engagement, retention, and revenue. Motivated to drive data-driven customer experiences and resilient engineering practices, fostering continuous improvement and long-term value creation.
Skills
Ai/ml/genai: Generative Ai Applications, Llms (Gpt-4, Llama), Huggingface, Pytorch, Tensorflow/keras, Peft, Langchain, Langgraph, Langfuse, Guardrails.ai, Rag Pipelines (Faiss, Pgvector, Chromadb), Vector Databases, Conversational Ai, Agentic Ai, Fine-tuning, Prompt Engineering, Llmops, Mlops
Programming: Python (Fastapi, Pytorch, Ml/ai), Node.js/typescript, Java (Spring Boot), Golang, C/c++, Angular, React
Cloud & Infrastructure: Aws, Azure, Gcp, Kubernetes, Docker, Openshift, Terraform, Argocd, Helm, Ci/cd (Github Actions, Gitlab Ci, Jenkins), Devsecops, Infrastructure-as-code, Ssdlc
Data & Platforms: Apache Airflow, Databricks, Dbt, Snowflake, Mlflow, Whylabs, Langsmith, Bloomberg Data Feeds, Rest/graphql Apis
Observability: Prometheus, Grafana, Dynatrace, Datadog, Newrelic, Honeycomb, Itsm
Engineering Practices: Secure Sdlc, Dependency Scanning, Static Code Analysis, Automated Testing, Domain-driven Design, Event-driven Architecture, Agile Delivery, Sla/slo, Dora Metrics
Ai Transformation & Strategy: Artificial Intelligence, Machine Learning, Deep Learning, Generative Ai, Llm, Large Language Models, Conversational Ai, Multi-agent Systems, Ai Strategy, Ai Roadmap, Ai Adoption, Ai Literacy, Digital Transformation, Data-driven Transformation, Ai Enablement, Ai Governance, Responsible Ai, Ethical Ai, Fairness, Bias Mitigation, Transparency, Compliance, Gdpr, Data Privacy, Data Protection, Enterprise Ai, Ai Scaling, Pilot To Production, Mvp To Production, Ai Value Delivery, Roi, Ai Kpis, Ai Metrics, Performance Monitoring, Model Monitoring, Model Governance, Mlops, Llmops
Ai Platforms & Tools: Mlflow, Databricks, Airflow, Tensorflow, Pytorch, Scikit-learn, Huggingface, Langchain, Vector Databases, Rag, Pgvector, Faiss, Knowledge Bases
Process & Automation: Workflow Automation, Process Automation, Business Process Redesign, Ai Integration, Business Process Optimization, Change Management, Stakeholder Alignment, Cross-functional Collaboration, Business-it Alignment, Product Management, Program Management, Agile, Scrum, Safe, Iterative Delivery, Continuous Delivery, Ci/cd, Devops, Devsecops
Cloud & Operations: Cloud Platforms (Aws, Azure, Gcp), Kubernetes, Docker, Terraform, Argocd, Openshift, Microservices, Event-driven Architecture, Real-time Inference, Scalable Ai Systems, Resilience, High Availability, Observability, Monitoring, Prometheus, Grafana, Dynatrace, Newrelic, Datadog, Secure Sdlc, It Strategy, Innovation Management, Emerging Technologies, Vendor Management, Ai Platforms, Ai Tools, Finops, Cost Optimization, Cloud Governance, Efficiency Gains, Productivity Improvement
Customer & Product: Customer Experience, User Engagement, Search And Recommendation, Personalization, Ranking Algorithms, A/b Testing, Experimentation Frameworks, Data Engineering, Data Pipelines, Etl, Data Lake, Data Warehouse, Sql, Python, Typescript, Java, Jvm, React, Node.js
Leadership & Enablement: Leadership, People Management, Talent Development, Team Scaling, Mentoring, Coaching, Career Frameworks, Culture Building, Ai Evangelism, Ai Advocacy, Training, Enablement Programs, Organizational Change, Communication, Vision, Strategy, Execution, Value Creation
Domain Interests: E-mobility, Sustainable Mobility, Healthcare Ai, Healthtech, Patient Care, Workflow Simplification
Languages
Education
Technical University of Munich (TUM)
M.Sc. Computer Science (Informatics) · Computer Science (Informatics) · Munich, Germany
North South University
B.Sc. Computer Science · Computer Science · Dhaka, Bangladesh
Certifications & licenses
Azure Gen AI Associate
Microsoft Azure
Generative AI With Large Language Models
DeepLearning.AI
Supervised Machine Learning
Stanford/DeepLearning.AI
AWS Certified Cloud Practitioner
TOGAF
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