Akintola Williams Deloitte is the Deloitte Touche Tohmatsu Limited (DTTL) member firm in Nigeria and the oldest indigenous professional services firm in Nigeria. The firm was established in 1952 by Mr. Akintola Williams, FCA, CFR, CBE, the doyen of the accountancy profession in Nigeria. Our approach to corporate responsibility is shaped by the recognition...
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Lead discussions with business and functional analysts to understand requirements and assess integration impacts on business architecture. Prepare technical architecture and design, clarify requirements, and resolve ambiguities. Develop solutions in line with established technical designs, integration standards, and quality processes. Create and enforce technical design and development guides, templates, and standards. Facilitate daily scrum meetings, manage deliverables, and prepare weekly status reports for leadership review. Conduct detailed deliverable reviews and provide technical guidance to team members. Collaborate with onsite clients, coordinators, analysts, and cross-functional teams. Design templates or scripts to automate routine development or operational tasks.
Key Responsibilities:
- Design and Development: Architect, build, and optimize agentic AI systems (e.g., autonomous agents, multi-agent frameworks, LLM-powered agents).
- Integrate agentic AI solutions with existing enterprise platforms and workflows.
- Research and Experimentation: Evaluate emerging agentic AI models, frameworks, and toolkits.
- Prototype and benchmark agentic AI solutions for scalability, robustness, and safety.
- Deployment and Monitoring: Deploying agentic AI agents in production environments, ensuring reliability and performance.
- Monitor agent behaviors, diagnose anomalies, and refine agent policies as needed.
- Developed feedback loops for continuous agent improvement.
- Ethics and Governance: Ensure agentic AI solutions comply with ethical standards, regulatory requirements, and organizational policies.
- Communicate complex technical concepts to non-technical audiences.
Qualifications
- A bachelor’s degree in computer science, software engineering, or a related discipline with a minimum of Second Class Upper/Upper Credit division.
- Have a minimum of five credits in WASSCE Ordinary Level/NECO subjects or acceptable equivalent examination, including Mathematics and English Language in one sitting only.
- 6 - 10 years of hands-on experience in Artificial Intelligence, Machine Learning, or related field.
- Knowledge of developing Gen AI or AI/ML solutions from use case to production and an understanding of agentic or autonomous systems.
- Strong understanding of Infrastructure and DevOps related to Gen AI Use case deployments including Cloud environments, LLM Hosting, CICD deployments, docker and Kubernetes clusters.
- Proficiency in Python development and FastAPI/Flask framework along with SQL
- Familiarity with agentic AI frameworks and concepts - LangChain, LangGraph, AutoGen, Model Context Protocol (MCP), LLMs, Chain of Thought prompting, knowledge store, embeddings.
- Autonomous agent development using cloud-based AI services.
- Prompt engineering techniques and fine-tuning.
- Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems.
- Experience with cloud platforms (AWS, Azure, GCP) and deploying AI solutions at scale.
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AI & Engineering leverages cutting-edge engineering capabilities to help build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These insights are powered by engineering for business advantage, helping transform mission-critical operations.
Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients’ achievements. You’ll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to business. Your contributions help Deloitte client service teams improve financial performance, accelerate new digital ventures, and fuel growth through innovation.
Key Responsibilities:
- Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations.
- Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, component design, development, unit testing, integrations, and support.
- Engineering Craftsmanship: Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations. Stay hands-on, self-driven, and continuously learn new approaches, languages, and frameworks with significant focus on infusing AI/ML/GenAI where possible/appropriate. Create technical specifications, and write high-quality, supportable, scalable code ensuring all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams.
- Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
- Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a learning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions.
- Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation.
- Advanced Technical Proficiency: Possess deep expertise in modern software engineering practices and principles, including AI/ML/GenAI, Agile methodologies and DevSecOps to deliver daily product deployments using full automation from code check-in to production with all quality checks through SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate understanding of the full lifecycle product development, focusing on continuous improvement and learning.
- Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff.
- Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives.
- Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions.
Qualifications
- A bachelor’s degree in computer science, software engineering, or a related discipline with a minimum of Second Class Upper/Upper Credit division. A Masters degree is an added advantage.
- Have a minimum of five credits in WASSCE Ordinary Level/NECO subjects or acceptable equivalent examination, including Mathematics and English Language in one sitting only.
- Strong software engineering foundation with deep understanding of OOPs, data-structure, algorithms, code instrumentations, beautiful coding practices etc.
- Minimum of 5 years of experience with AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches like Prompt Engineering, fine-tuning, etc.
- Proven experience in: Python, R, TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc.
- Proven experience with big data technologies, Angular, React, NodeJS, Python, C#, .NET Core, Java, Golang, SQL/NoSQL.
- Proven experience with cloud-native engineering, using FaaS/PaaS/micro-services on cloud hyper-scalers like Azure, AWS, and GCP.
- Strong understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, etc.
- Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.
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As a Data Engineering Manager, you will lead the design, build, and scale of enterprise-grade data infrastructure and pipelines to power advanced analytics, AI solutions, and AI transformations across Tier-1 clients on the African continent. You will work at the intersection of business strategy and technical delivery, guiding multidisciplinary teams to enable data-driven decision-making and measurable business impact.
You will be responsible for:
- Architecting scalable, secure, and high-performance data platforms
- Leading the design and development of robust ingestion, transformation, and governance pipelines
- Managing project timelines and deliverables across diverse industry engagements
- Coaching data engineers and analysts to deliver client-ready solutions
- Collaborating with AI/ML specialists, solution managers, and client stakeholders to translate strategic needs into modern data capabilities
- Lead and own data engineering workstreams across AI transformation, analytics modernisation, and digital core rebuilds
- Design and implement data pipelines using modern architectures (e.g., Delta Lake, Data Mesh, Data Lakehouse)
- Drive data modelling, data quality, and metadata management best practices aligned to business KPIs.
- Build, manage, and scale cloud-native data infrastructure (e.g., on AWS, GCP, Azure)
- Mentor junior engineers, oversee code reviews, and ensure delivery quality to tier-1 consulting standards.
- Translate business and industry requirements into scalable data engineering solutions
- Partner with AI, strategy, and business consulting teams to deliver end-to-end data value realisation.
Qualifications
- A bachelor’s degree in computer science, software engineering, or a related discipline with a minimum of Second Class Upper/Upper Credit division.
- Have a minimum of five credits in WASSCE Ordinary Level/NECO subjects or acceptable equivalent examination, including Mathematics and English Language in one sitting only.
- Minimum of 8 years of experience in data engineering, with at least 2 years in a team leadership or technical management role
- Proficient in building modern ETL/ELT pipelines using tools like Apache Spark, DBT, Kafka, Airflow
- Strong programming skills in Python and SQL (Scala/Java a plus)
- Deep experience with cloud data ecosystems (e.g., AWS Redshift/Glue, GCP BigQuery/Dataflow, Azure Synapse)
- Strong understanding of data warehousing, data lakes, streaming, and batch architecture
- Experience with CI/CD for data, testing frameworks, and infrastructure-as-code (Terraform, etc.)
- Familiarity with data governance and security frameworks in regulated industries (e.g., FSI, healthcare)
- Previous experience in a top-tier consulting environment or client-facing data role
- Exposure to AI/ML deployment pipelines, MLOps, or analytics.
- Experience in delivering data modernization programs at enterprise scale
go to method of application »
As a Full-stack Software Engineer, you will actively engage in your engineering craft, taking a hands-on approach to multiple high-visibility projects. Your expertise will be pivotal in delivering solutions that delight customers and users, while also driving tangible value for Deloitte's business investments. You will leverage your extensive engineering craftmanship across multiple programming languages and modern frameworks, consistently demonstrating your strong track record in delivering high-quality, outcome-focused solutions. The ideal candidate will be a dependable team player, collaborating with cross-functional teams to design, develop, and deploy advanced software solutions.
Key Responsibilities:
- Outcome-Driven Accountability: Embrace and drive a culture of accountability for customer and business outcomes. Develop engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality, lean designs and implementations.
- Technical Leadership and Advocacy: Serve as the technical advocate for products, ensuring code integrity, feasibility, and alignment with business and customer goals. Lead requirement analysis, component design, development, unit testing, integrations, and support.
- Engineering Craftsmanship: Maintain accountability for the integrity of code design, implementation, quality, data, and ongoing maintenance and operations. Be hands-on, self-driven, and continuously learn new approaches, languages, and frameworks. Create technical specifications, and write high-quality, supportable, scalable code ensuring all quality KPIs are met or exceeded. Demonstrate collaborative skills to work effectively with diverse teams.
- Customer-Centric Engineering: Develop lean engineering solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
- Incremental and Iterative Delivery: Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions.
- Cross-Functional Collaboration and Integration: Work collaboratively with empowered, cross-functional teams including product management, experience, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation.
- Advanced Technical Proficiency: Possess deep expertise in modern software engineering practices and principles, including Agile methodologies and DevSecOps to deliver daily product deployments using full automation from code check-in to production with all quality checks through SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate understanding of the full lifecycle product development, focusing on continuous improvement and learning.
- Domain Expertise: Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs, architectures, and UX/UI designs into technical specifications and code. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff.
- Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives.
- Engagement and Collaborative Co-Creation: Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions.
Qualifications
- Have a minimum of five credits in WASSCE Ordinary Level/NECO subjects or acceptable equivalent examination, including Mathematics and English Language in one sitting only.
- A bachelor’s degree in computer science, software engineering, or a related discipline with a minimum of second class upper/upper credit division.
- Strong software engineering foundation with the understanding of OOPs, data-structure, algorithms, code instrumentations, beautiful coding practices, etc.
- 7+ years proven experience with most of the following: Angular, React, NodeJS, Python, C#, .NET Core, Java, Golang, SQL/NoSQL.
- 7+ years of experience with cloud-native engineering, using FaaS/PaaS/micro-services on cloud hyper-scalers like Azure, AWS, and GCP.
- Strong understanding of methodologies & tools like, XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, etc. to deliver high quality products rapidly.
- Strong preference will be given to candidates with experience in AI/ML and GenAI.
- Experience exceeding 5 years with multiple cloud providers (AWS, Azure, GCP).
- Advanced skills in serverless and containerized architectures across public clouds.
- Expertise implementing and optimizing highly available, scalable solutions using a broad suite of AWS / GCP / Azure services.
- Prior transformation or modernization experience, leading a team as a technical lead.
- Skilled at translating business requirements into robust, maintainable technical solutions as part of high-performing, cross-functional teams.
- Track record of effective code reviews, ensuring code quality, security, and alignment with best practices.
- Strong written and verbal communication skills, evidenced by experience collaborating across technical and non-technical teams.
- Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.
Method of Application
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