Solution Architect (Pre-Sales, Delivery & AI Enablement)

At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed. And now we are looking for a Solution Architect (Pre-Sales, Delivery & AI Enablement) to join us as part of our team. About the role This is an internal architecture role at the intersection of pre-sales, delivery and AI enablement. Around 60% of our incoming pre-sales requests now involve AI/ML (OCR, Computer Vision, fraud detection, RAG and agentic solutions), so we need an architect who can shape, challenge, estimate and sell these solutions — not a narrow ML specialist. You will work across multiple engagements and domains rather than a single product, and collaborate closely with our in-house ML/MLOps team rather than owning deep ML modelling yourself. The role has three focuses: • Pre-Sales & Estimation — shaping and defending solutions and estimates for new engagements. • Solution Architecture & SDLC ownership — owning end-to-end architecture and the overall target-architecture vision across engagements. • AI Enablement — helping teams adopt AI-assisted development: selecting the right tools/harness per project, onboarding, upskilling, and monitoring adoption. Technical stack • Languages & platforms: Java, C#, Python, Node.js — multi-stack breadth, without being locked into one ecosystem. • Architecture & integration: microservices, event-driven and messaging patterns, scalable APIs, enterprise integrations, data-analytical systems. • Cloud: AWS, GCP or Azure; managed IaaS/PaaS/SaaS services. • Containers & orchestration: Docker, Kubernetes. • Data & search: PostgreSQL, MS SQL, distributed caching and replication (Redis), enterprise search (Elasticsearch), vector stores for retrieval. • AI/GenAI: LLM orchestration, multi-agent frameworks, RAG pipelines, evaluation and guardrails; OCR/Computer Vision and fraud-detection solutions delivered together with ML engineers. • AI-assisted development: AI coding tools and harnesses (e.g., BMAD, Spec Kit), agentic workflows, context management. • Architecture practices: ADRs, target/transition-state and system diagrams, NFRs and the "-ilities", secure-by-design, CI/CD. Work Environment Fully remote, with a flexible schedule and the requirement to attend all key team and client meetings. As a qualified expert, You will 1. Pre-Sales & Estimation • Lead the technical discovery process and design robust, scalable, cost-effective solutions for proposals, RFI/RFP responses and new client engagements. • Own estimation end-to-end: turn Sales’ discoveries into engineering-grounded estimates; challenge and correct estimates that are not grounded in real delivery effort. • Act as the bridge between Sales and Delivery — ensure estimates reflect engineers’ input and that the delivery team understands and can execute what was sold. • Prepare technical sections of proposals: solution descriptions, architecture diagrams, assumptions, risks and delivery approach. • Be the primary technical point of contact for prospective clients, clearly articulating the solution, technology stack and implementation strategy to technical and non-technical stakeholders. • Produce an architecture vision, roadmap, MVP definition and high-level delivery plan during discovery/inception. • Where AI/ML is involved, scope and estimate it correctly, working with our in-house ML engineers for deep modelling input. 2. Solution Architecture & Delivery • Own and evolve the end-to-end architecture of solutions (backend services, data storage, integrations, cloud infrastructure), explicitly addressing the "-ilities": scalability, availability, recoverability, maintainability, extensibility, portability, usability and security. • Hold and promote the target architecture vision across the portfolio; run architecture reviews and design workshops with delivery teams. • Drive system evolution toward well-defined target and transition (interim) states, using system diagrams that give engineering teams a clear, actionable execution path. • Propose pragmatic, balanced technical decisions in areas such as build vs. buy, now vs. later and refactor vs. rebuild, and document the trade-offs behind them. • Define and maintain architecture artefacts: high-level and system diagrams, data flows, non-functional requirements, technical guidelines and ADRs — and author AI-ready solution specifications as part of the design lifecycle. • Provide hands-on guidance: design sessions, review of critical technical decisions and PRs, spikes and PoCs when needed. • Ensure the solution meets scalability, security, availability and cost-efficiency expectations, and simplify otherwise complex problems into pragmatic designs. • Participate in starting new projects from scratch: scope, architecture approach, MVP slice and key technical decisions. 3. AI Enablement (a key differentiator for this role) • Understand AI-assisted development deeply: how agents and agentic workflows work, how LLMs behave, context management, and the trade-offs/gaps of AI coding tools and harnesses (e.g., BMAD, Spec Kit) — including limitations such as incomplete TDD, combined dev+test single-agent roles, and context handling. • Recommend which AI dev tools/harness fit which class of project, phase and SDLC — and where they do not; identify gaps and judge whether they are critical for a given project. • Customize and guide the harness and agent setup to fit a team’s SDLC, rather than blindly adopting a ready-made flow. • Support AI enablement across projects: initial guidance, onboarding of teams (incl. SPD Labs), upskilling engineers and AI champions, and monitoring adoption while answering questions along the way. • Drive system innovation by leveraging AI as a core enabler — prototyping high-impact capabilities to prove technical feasibility and steer future-ready architectural directions. • Provide early, defensible ballpark estimates using AI tooling to help qualify opportunities before deeper discovery. We’re looking for you if you have • 7+ years of hands-on software development experience with strong core engineering principles, including 3+ years designing complex software architectures for multi-stack environments. • Broad, hands-on engineering experience across the full SDLC: distributed systems, cloud-native architectures, scalable APIs, data-driven solutions and enterprise integrations. • Practical experience designing data solutions across relational databases, distributed caching, replication and enterprise search engines. • Experience architecting on at least one major cloud platform using containerization and orchestration, plus a working map of managed cloud services and the habit of continuously learning new platforms, frameworks and libraries — commercial and open source. • Practical, hands-on understanding of AI/GenAI and agentic development — agents, LLM behaviour, context management, AI coding harnesses and their trade-offs. This is central to the role. • Ability to work effectively alongside ML engineers on AI/ML solutions (OCR/Computer Vision, fraud detection, RAG, agentic) — enough to scope, challenge and estimate, without being a deep ML modelling specialist. • A disciplined approach to architectural decision-making: systematically evaluating trade-offs, risks and technology pros/cons to deliver resilient, cost-effective solutions. • Strong estimation skills and the ability to defend estimates to both Sales and Delivery. • Proven ability to manage stakeholder expectations and build cross-organizational alignment, adapting from deep technical dives with engineers to non-technical dialogue with senior stakeholders. • Excellent communication and client-facing skills; people-oriented and comfortable guiding, onboarding and upskilling engineers — enablement is a core part of the job. • Strong analytical and problem-solving skills, with the ability to define technical solutions under tight deadlines and vague requirements. • Prior experience in pre-sales, technical discovery or solution consulting. • Experience coaching engineering teams and growing their ability to make high-quality autonomous software-design decisions. What’s in it for You Reveal great tech solutions Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling client growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients. Experience an agile and flexible working environment Enjoy the freedom of fully remote work with a flexible working schedule. Empower yourself with a stable workload and a stable income, supported by provided laptops and licensed software. We focus on lasting cooperation and unite result-oriented individuals who stand on a high-performance approach to work. Embrace the opportunity for personal and professional growth Benefit from performance and merit reviews, elevate your skills with personal development plans, and individual learnings through the corporate library, public speaking support, and more. Be among like-minded people Work with a team of one mind who cares about what they do and how they do. Collaborate with top-notch experts who are always ready to help and support you through any challenges. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Feel supported by your HR, and take advantage of our referral bonus program. Interview Steps: Pre-screening with recruiter Technical Screening. Technical Interview Manager Interview Interview with BizDev & Sales. Executive Interview.