ICFJ+ is looking for a full-time AI Solutions Architect, Business Development (BD) Systems to join the BD team for a non-profit organisation operating across Africa, the Middle East, Europe, and the USA. The selected candidate will work remotely (with US Eastern time-zone overlap preferred), reporting to the BD Senior Director and working closely with the DataLab, AI Sandbox, Engineering/Ops, and other relevant team leads.
ICFJ+ overview
Information should be power, but only when it’s relevant and reliable. Too often, it’s neither, leaving people unable to navigate complexities or make informed decisions. ICFJ+ was launched to change this. We cultivate civic intelligence – information that helps people make sense of their world and act constructively to shape it.
ICFJ+ is a global partnership between civic tech powerhouse Code for Africa (CfA), media support network International Center for Journalists and PROTO, a Delhi-/Doha-based systems builder. Our goal is to cultivate civic intelligence – helping people make sense of the world and act constructively to shape it.
Position Summary
ICFJ+ is modernizing how its BD team discovers, evaluates, and responds to funding and revenue generation opportunities—across institutional donors, philanthropic organizations, technology platforms, events, and high-net-worth individuals. This role will help make the organisation’s BD approach meaningfully faster and sharper across funding opportunities, without compromising the human judgment, donor relationships, compliance discipline, and responsible data use on which the work depends.
The AI Solutions Architect, Business Development Systems will design, prototype, and ship practical AI-enabled workflows across two main tracks:
- A proposal lifecycle toolkit.
- An AI-enriched CRM and relationship intelligence layer.
This is a hands-on build-and-ship role that is responsible for the BD-specific application layer that sits on top of ICFJ+’s existing tools, data, knowledge assets, and shared AI platforms. This includes the workflows, integrations, retrieval pipelines, prompts, review interfaces, and Airtable/CRM structures that make BD work faster and better informed.
Note: The position will not own the underlying model stack, shared infrastructure, enterprise data warehousing, or organization-wide AI policy. Those sit with AI Sandbox, DataLab, and Engineering/Ops respectively. However, the AI Solutions Architect will collaborate closely with those teams.
Key Responsibilities
The AI Solutions Architect will design and ship four practical systems integrated with ICFJ+’s existing Google Workspace, Airtable, Slack, CRM, shared drives, and approved AI tooling.
1. Opportunity Fit Evaluator
Inputs: Donor portals, newsletters, mailing lists, partner forwards, procurement notices, and other opportunity sources, using APIs where available and scheduled ingestion or lightweight parsing where APIs are not available.
Behavior: Scores each opportunity against a defined BD rubric, including organizational capabilities, thematic fit, geographic focus, donor eligibility, compliance requirements, risk level, and strategic value. Confirms hard eligibility gates early and flags weak-fit, ineligible, or high-risk opportunities before staff invest significant time.
Output: A ranked opportunity queue with rationale, confidence signals, eligibility notes, risk flags, and suggested next steps. The system should also surface relevant past proposals, technical experience, consortium partners, sub-awardees, donor history, and relationship context from the CRM and knowledge base.
Human gate: BD reviewers accept, reject, escalate, or request more information before an opportunity advances to capture planning.
2. Application Project Manager
Inputs: Donor solicitations, RFPs, NOFOs, application guidelines, eligibility documents, compliance instructions, budget templates, annex requirements, and submission portals.
Behavior: Parses solicitation materials and extracts required deliverables, attachments, deadlines, compliance requirements, formatting rules, submission steps, budget requirements, and review dependencies. Converts these into a structured work plan, proposal calendar, and responsibility matrix.
Output: A dynamic application tracker with tasks, owners, deadlines, dependencies, review checkpoints, and submission requirements, usable in the BD team’s preferred workflow tools, such as Airtable, Slack, email, or an approved lightweight review interface.
Human gate: BD leadership or assigned proposal leads review and approve the work plan before assignments, reminders, or downstream automations are triggered.
3. Proposal Scaffolding Tool
Inputs: Donor priorities, solicitation documents, concept notes, prior proposals, capability statements, approved technical language, partner profiles, lessons learned, program examples, evaluation criteria, and relevant institutional knowledge.
Behavior: Retrieves relevant knowledge assets and generates early-stage proposal scaffolds, including concept frameworks, narrative outlines, partner discussion prompts, donor-aligned talking points, compliance-aware section prompts, and draft review questions. Supports staged critique aligned to donor priorities, review criteria, and compliance expectations.
Output: Structured proposal-starting materials that help BD and program staff move faster from opportunity assessment to concept development. Outputs should include source references where possible and distinguish between retrieved institutional material, AI-generated synthesis, and areas requiring human judgment.
Human gate: BD and technical leads review, revise, approve, or reject generated scaffolds before they are used in partner discussions or proposal drafting.
4. CRM Relationship Intelligence Layer
Inputs: Existing CRM or Airtable records, donor and partner contact data, engagement notes, prior opportunities, proposal history, event participation, conference intelligence, relationship ownership information, and approved external or internal data sources.
Behavior: Structures and enriches relationship intelligence so BD staff can understand donors, partners, contacts, decision pathways, and engagement history. Captures relationship strength, our strategic role with each donor, prior collaboration history, pathway mapping to decision-makers, consortium partner and sub-awardee fit signals, event and conference attendance intelligence, pre-RFP signals, Terms of Reference shaping opportunities, and ownership rules for data maintenance.
Output: An Airtable-anchored or CRM-connected relationship intelligence layer that surfaces useful context during opportunity screening, capture planning, partner outreach, and proposal development. The system should make relationship data easier to maintain, not harder.
Human gate: Staff review and confirm sensitive relationship notes, ownership fields, inferred connections, and strategic recommendations before they are treated as reliable CRM intelligence.
Core Competencies
- Able to Design Practical, Maintainable AI Workflows: Favor integration with existing systems over new stacks. Use APIs, automation tools, low-code platforms, or lightweight custom code where appropriate. Calibrate evaluation and quality checks to the consequence of errors. (Familiarity with Claude, OpenAI, LangGraph, n8n, Zapier, Make, Airtable automations, and vector databases is highly useful).
- Able to Design for Human Control: Ensure human-in-the-loop oversight, especially on consequential decisions. Design approval gates, review interfaces, audit trails, escalation paths, and override mechanisms so staff can correct, reject, or question AI outputs before downstream actions occur.
- Can Drive Adoption with Non-Technical Users: Lead discovery and feedback sessions, train users, write SOPs and handoff materials, and design around real staff capacity and existing work habits. Track focused adoption and quality metrics (e.g., time saved, eligibility scoring accuracy, user override rates) and iterate based on data.
- Can Build for Handoff from Day One: Set up monitoring and alerts for workflow failures, broken integrations, data anomalies, permission issues, stale knowledge sources, and degraded AI outputs. Document integration logic, assumptions, risks, and maintenance requirements for ultimate transition to the internal downstream owner.
- Able to Maintain Responsible AI, Data Governance, and Privacy: Define practical guardrails to protect sensitive organizational information, donor intelligence, proposal materials, and PII. Ensure outputs are traceable to source materials, document limitations, and coordinate closely with data protection leads.
Qualifications and Skills
Required:
- 3+ years of experience building and shipping internal systems, workflow automation, or AI-enabled tools in real organizational settings, with demonstrated recent experience deploying LLM-enabled workflows, RAG systems, agentic automation, or AI assistants that real users actually use.
- Strong experience integrating productivity, CRM, and knowledge systems such as Google Workspace, Airtable, Slack, shared drives, email, CRMs, or document repositories, and a preference for designing on top of existing infrastructure rather than defaulting to custom builds.
- Strong process and workflow design skills, including the ability to map how work actually happens, identify friction points, and design human-in-the-loop systems with approval gates, escalation paths, audit trails, and override mechanisms.
- Demonstrated ability to drive adoption among non-technical users through discovery sessions, training, documentation, feedback loops, and iterative improvement.
- Sound data-handling judgment, including PII awareness, access control, source traceability, confidentiality, and responsible use of third-party AI tools.
- Strong written communication skills, including the ability to document technical designs, write SOPs, and produce handoff materials for non-technical stakeholders. A pragmatic, build-and-ship orientation: comfort moving from ambiguity to working systems quickly, and willingness to sit with end users to understand their work before designing for it.
Preferred Qualifications
- Experience working in or with donor-funded environments such as nonprofit, international development, journalism, media support, or civic technology, including familiarity with proposal operations, bid/no-bid workflows, donor compliance, capture planning, and partner coordination. Experience with workflow automation platforms such as n8n, Zapier, Make, Airtable automations, or comparable tools.
- Experience with RAG systems, vector databases, document retrieval, metadata design, or knowledge-base maintenance, particularly in contexts where keeping knowledge current is a design constraint.
- Experience with document parsing of PDFs, DOCX files, donor solicitations, compliance matrices, and other unstructured content.
- Experience with prompt evaluation, AI quality assurance, model testing, red-teaming, hallucination monitoring, or structured output validation.
- Experience designing CRM enrichment, relationship intelligence, partner mapping, donor engagement tracking, or stakeholder mapping, and working knowledge of API hygiene, scoped credentials, OAuth flows, secrets management, and vendor security review.
How to Apply: Please fill in this form by 10 July 2026.
At ICFJ+, we don’t just accept differences – we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. ICFJ+ is proud to be an equal opportunity workplace and is an affirmative action employer. If you have a disability or special need that requires accommodation, please let us know.